QUANTIFYING GAS IN PASSIVE OPTICAL GAS IMAGING
20170363541 · 2017-12-21
Inventors
Cpc classification
G01N21/3518
PHYSICS
International classification
Abstract
A method and a system to quantify gas in a thermal imaging device, said method comprising obtaining a gas-absorption-path-length image as a scene difference infrared image based on a gas infrared image and a scene background infrared image substantially depicting the same scene and generating a quantified scene difference infrared image based on said scene difference infrared image and a predefined gas-quantifying relation.
Claims
1. A method for quantify gas in an image of a scene having a background and a possible occurrence of gas, the method comprising: obtaining a gas-absorption-path-length image as a scene difference infrared image, the gas-absorption-path-length image determined based on a gas infrared image and a scene background infrared image depicting a substantially same scene; and generating a quantified scene difference infrared image based on the scene difference infrared image and a predefined gas-quantifying relation (GQR).
2. The method of claim 1, wherein the gas-quantifying relation describes a relationship between scene difference infrared image pixel values and quantified scene difference infrared image pixel values in the form of a concentration length product expressed in parts per million*meter (ppm*m).
3. The method of claim 2, wherein the gas-quantifying relation is generated by operations comprising: measuring a first set of quantified scene difference infrared image pixel values for known gas concentrations, gas-absorption path lengths, gas temperatures, and background temperatures; and expanding the first set to a second larger set by applying a curve fitting technique, the gas-quantifying relation comprising a relationship between a set of scene difference infrared image pixel values and the second larger set of quantified scene difference infrared image pixel values.
4. The method of claim 1, wherein: the obtaining of the gas-absorption-path-length image comprises determining a high absorption wavelength band A and a low absorption wavelength band B to improve contrast in a generated gas-absorption-path-length image based on estimated image noise, a predetermined absorption spectrum of a gas, an estimated gas temperature, and an estimated background temperature; the high absorption wavelength band A includes an absorption wavelength band G from the absorption spectrum; and the low absorption wavelength band B at least partially overlaps the high absorption wavelength band A.
5. The method of claim 4, wherein the obtaining of the gas-absorption-path-length image further comprises: generating infrared imaging system control data to control the capturing, by an infrared imaging system, of the gas infrared image of the scene comprising intensity of infrared radiation within the high absorption wavelength band A and of the background infrared image of the scene comprising intensity of infrared radiation within the low absorption wavelength band B; and generating the gas-absorption-path-length image based on the gas infrared image and the background infrared image.
6. The method of claim 4, wherein: the estimated image noise comprises a Noise Equivalent Temperature Difference (NETD); and the quantified scene difference infrared image pixel values comprise temperature values.
7. The method of claim 4, wherein: the high absorption wavelength band A is determined with a lower endpoint in a range between and including about 6 μm and 7.8 μm; and the high absorption wavelength band A is determined with a higher endpoint in a range between and including about 8 μm and 9.6 μm.
8. The method of claim 4, further comprising: determining a water related wavelength band C to improve contrast in the generated gas-absorption-path-length image based on a predetermined water absorption spectrum, wherein the water related wavelength band C includes at least a local maximum of the water absorption spectrum and excludes high absorption wavelength band A and low absorption wavelength band B; and generating infrared imaging system control data to control the capturing of a water infrared image of the scene by an infrared imaging system, wherein the water infrared image comprises intensity of infrared radiation within the water related wavelength band C, wherein the generating of the quantified scene difference infrared image is further based on the water infrared image.
9. A thermal imaging device for quantify gas in an image of a scene having a background and a possible occurrence of gas, the thermal image device comprising: an infrared (IR) imaging system configured to capture a gas infrared image and a scene background infrared image depicting a substantially same scene; a memory; and a processor communicatively coupled to the IR imaging system and the memory, the processor being configured to: obtain a gas-absorption-path-length image as a scene difference infrared image, the gas-absorption-path-length image determined based on the gas infrared image and the scene background infrared image; and generate a quantified scene difference infrared image based on the scene difference infrared image and a predefined gas-quantifying relation (GQR).
10. The thermal imaging device of claim 9, wherein the gas-quantifying relation describes a relationship between scene difference infrared image pixel values and quantified scene difference infrared image pixel values in the form of a concentration length product expressed in parts per million*meter (ppm*m).
11. The thermal imaging device of claim 10, wherein the gas-quantifying relation is generated by operations comprising: measuring a first set of quantified scene difference infrared image pixel values for known gas concentrations, gas-absorption path lengths, gas temperatures, and background temperatures; and expanding the first set to a second larger set by applying a curve fitting technique, the gas-quantifying relation comprising a relationship between a set of scene difference infrared image pixel values and the second larger set of quantified scene difference infrared image pixel values.
12. The thermal imaging device of claim 9, wherein the infrared imaging system is configured and/or controllable to: capture the gas infrared image of the scene comprising intensity of infrared radiation within a high absorption wavelength band A for a gas; and capture the background infrared image of the scene comprising intensity of infrared radiation within a low absorption wavelength band B for the gas.
13. The thermal imaging device of claim 12, wherein the infrared imaging system comprises: a first infrared imaging system configured and/or controllable to capture the gas infrared image; and a second infrared imaging system configured and/or controllable to capture the scene background infrared image.
14. The thermal imaging device of claim 12, wherein: the high absorption wavelength band A and the low absorption wavelength band B are determined so as to improve contrast in the generated gas-absorption-path-length image based on estimated image noise, a predetermined absorption spectrum of the gas, an estimated gas temperature, and an estimated background temperature; the high absorption wavelength band A includes an absorption wavelength band G from the absorption spectrum; and the low absorption wavelength band B at least partially overlaps the high absorption wavelength band A.
15. The thermal imaging device of claim 14, wherein the estimated image noise comprises a Noise Equivalent Temperature Difference (NETD), wherein the quantified scene difference infrared image pixel values comprise temperature values.
16. The thermal imaging device of claim 12, wherein: the high absorption wavelength band A is determined with a lower endpoint in a range between and including about 6 μm and 7.8 μm; and the high absorption wavelength band A is determined with a higher endpoint in a range between and including about 8 μm and 9.6 μm.
17. The thermal imaging device of claim 12, wherein the processor is further configured to obtain the gas-absorption-path-length image by operations comprising: generating control data to control the capturing of the the gas infrared image and the background infrared image by the infrared imaging system; and generating the gas-absorption-path-length image based on the gas infrared image and the background infrared image.
18. The thermal imaging device of claim 12, wherein: the infrared imaging system is further configured and/or controllable to capture a water infrared image of the scene comprising intensity of infrared radiation within a water related wavelength band C; the water related wavelength band C includes at least a local maximum of a water absorption spectrum and excludes the high absorption wavelength band A and the low absorption wavelength band B; and the processor is further configured to generate the quantified scene difference infrared image further based on the water infrared image.
19. The thermal imaging device of claim 18, wherein the water related wavelength band C is determined based on the water absorption spectrum so as to improve contrast in the generated gas-absorption-path-length image.
20. A non-transitory computer-readable medium storing instructions which, when executed by a processor of a thermal imaging device, cause the thermal imaging device to perform a method of quantifying gas in an image of a scene having a background and a possible occurrence of gas, the method comprising: obtaining a gas-absorption-path-length image as a scene difference infrared image, the gas-absorption-path-length image determined based on a gas infrared image and a scene background infrared image depicting a substantially same scene; and generating a quantified scene difference infrared image based on the scene difference infrared image and a predefined gas-quantifying relation (GQR).
Description
BRIEF DESCRIPTION OF THE DRAWINGS
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[0049] Embodiments of the present disclosure and their advantages are best understood by referring to the detailed description that follows. It should be appreciated that like reference numerals are used to identify like elements illustrated in one or more of the figures.
DETAILED DESCRIPTION
Introduction
[0050] The disclosure relates to imaging and visualizing quantified gas using infrared IR sensors or detectors and image processing. An example of a use case is the inspection with a thermal imaging device of a part of an industrial complex handling gas.
[0051] In particular the disclosure relates to passive gas imaging that uses thermal background radiation within the infrared region and can be used to image gas for example against a cold background, in this case imaging thermal emission or radiation from the gas, or used against a warm background, in that case imaging absorption by the gas of thermal radiation from the background. Imaging of gas is based on the difference in gas temperature T.sub.G and background temperature T.sub.B, hereinafter referred to as gas to background temperature difference ΔT. However, the sensitivity of a thermal imaging system is dependent on the difference in gas temperature T.sub.G and background temperature T.sub.B,
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[0053] In one or more embodiments, a gas-absorption-path-length image representing the length of the path of radiation from the scene background 110 through a gas occurrence in the scene can be generated based on a gas infrared image, a background infrared image and optionally the temperature difference parameter ΔT 130. In yet an embodiment a pixel value 181 derived from processed pixel values in a gas-absorption-path-length image is at least used to determine a quantified pixel value 182 indicative of concentration length by gas-quantifying relation GQR 180 in the form of a concentration length or concentration-path length product CL in parts per minute*meter ppm*m. In yet an embodiment, quantified gas is visualized in a quantified gas visualization image presentable or presented to the user on a display, this image being based on pixel values of the gas-absorption-path-length image. In yet an embodiment a background temperature T.sub.B 122 derived from a pixel value in a background infrared image and a gas temperature T.sub.G 121 derived from a pixel value in a gas infrared image are used to determine the temperature difference parameter ΔT 130.
[0054] In one or more embodiments, the gas temperature T.sub.G is estimated based on a measured ambient air temperature retrieved from an ambient air temperature sensor and/or based on a previously captured gas IR image that comprises a representation of the intensity of infrared radiation within a first wavelength band A substantially including wavelengths of infrared radiation with high absorptance values for the gas in an absorption spectrum and/or low transmittance values in a transmission spectrum. In other words, the first wavelength band A is a high absorption wavelength band that includes wavelengths significantly affected by the presence of the gas to be imaged. In a case where the gas has a temperature higher than the ambient air temperature or the background temperature there is radiation from the gas in an emission spectrum. The first wavelength band A is herein also called high absorption wavelength band A.
[0055] In one or more embodiments, the background temperature T.sub.B is estimated based on a previously captured background IR image that comprises a representation of the intensity of infrared radiation within a second wavelength band B substantially including wavelengths of infrared radiation with low absorptance values for the gas in an absorption spectrum and/or high transmittance values in a transmission spectrum. In other words, the second wavelength band B is a low absorption wavelength band and/or a high transmission wavelength band that includes wavelengths insignificantly affected by the presence of the gas to be detected. The second wavelength band B is herein also called low absorption wavelength band B.
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[0058] By controlling the thermal imaging system to capture radiation in a high absorption wavelength band A including wavelengths significantly affected by the presence of the gas to be detected, and to capture radiation in a low absorption wavelength band B including wavelengths insignificantly affected by the presence of the gas to be detected, a background IR image and a gas IR image are generated. Based on the background IR image, on the gas IR image and dependent on a transmission spectrum 251 and/or on an absorption spectrum 241, a gas-absorption-path-length image with improved contrast is generated in a system with improved sensitivity and/or improved signal to noise ration.
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System Embodiments
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[0063] In embodiments, the thermal imaging device 170 comprises a processor 612
[0064] In embodiments, the thermal imaging device 170 comprises a first infrared (IR) imaging system 613 that is configured and/or controllable to capture infrared (IR) images in the form of IR image data values/pixel values, representing infrared radiation emitted from an observed scene within one or more selectable wavelength bands A, B or C. The infrared (IR) imaging system 613 is further communicatively coupled to a processor 612.
[0065] The first infrared (IR) imaging system 613 is further configured to receive control data and to trigger the capturing of an IR image of a scene within a selected wavelength band in response to said control data. The first infrared (IR) imaging system 613 is further arranged to send a signal frame or data frame of IR image data values representing a captured image to the processor 612. IR image data typically include data values for example represented in an instance of a data structure, such as an image data frame as mentioned. In embodiments, the processor/processing unit 612 is provided with specifically designed programming or program code portions adapted to control the processing unit to perform the steps and functions of one or more embodiments of the method and/or methods described herein.
[0066] The thermal imaging device 170 further comprises at least one memory 615 configured to store data values or parameters received from a processor 612 or to retrieve and send data values or parameters to a processor 612. A communications interface 616 is configured to send or receive data values or parameters to or from a processor 612 to or from external or internal units or sensors via the communications interface 616. An optional input device 617 is configured to receive an input or an indication from a user, e.g. an input of a user indicating a command to execute the imaging of a gas-absorption-path-length image.
[0067] In one or more embodiments, the thermal imaging device 170 further comprises a display 618 configured to receive a signal from a processor 612 and to display the received signal as a displayed image, e.g. to display a visual representation of a gas-absorption-path-length image to a user of the thermal imaging device 170. In one or more embodiments, the display 618 is integrated with a user input device 617 configured to receive a signal from a processor 612 and to display the received signal as a displayed image and receive input or indications from a user, e.g. by comprising touch screen functionality and to send a user input signal to said processor/processing unit 612.
[0068] In one or more embodiments, the thermal imaging device 170 further comprises an ambient air temperature sensor 619 configured to measure ambient air temperature and generate an ambient air temperature data value and provide the ambient air temperature data value to the processor 612 receiving, polling or retrieving the ambient air temperature data value. In one or more embodiments, the ambient air temperature sensor 619 is communicatively coupled to the processor 612 directly or via the communications interface 616, and may be provided as an external or an internal unit.
[0069] In one or more embodiments, the thermal imaging device 170 further optionally comprises a second infrared (IR) imaging system 614, preferably with properties and functions similar to those of the first infrared (IR) imaging system 612 described above. The second infrared (IR) imaging system 614 is similarly configured and/or controllable to capture infrared (IR) images in the form of IR image data values/pixel values, representing infrared radiation emitted from an observed scene within one or more selectable wavelength bands A, B or C. The second infrared (IR) imaging system 614 is further communicatively coupled to a processor 612, and is further configured to receive control data and to trigger the capturing of an IR image of a scene within a selected wavelength band in response to said control data. The second infrared (IR) imaging system 614 is further arranged to send a signal frame of IR image data values representing an infrared (IR) image to the processor 612.
[0070] Typically, the described infrared (IR) imaging systems 613, 614 each comprises an infrared (IR) optical system 6131, 6141, e.g. comprising a lens, possible zoom functionality and focus functionality 6131, together with a corresponding infrared (IR) sensor 6132, 6142, for example comprising a micro-bolometer focal plane array.
Examples of Controllable/Selectable Wavelength Bands
[0071] The described infrared (IR) imaging systems 613, 614 are configured and/or controllable to capture infrared (IR) images in the form of IR image data values/pixel values, representing infrared radiation emitted from an observed scene within a preferably continuous subset of a plurality of wavelength bands A, B or C. One or more of the wavelength bands may be at least partly overlapping.
[0072] In one example, wavelength band A is selected as 7-9 μm and wavelength band B is selected as 9-15 μm, where the first infrared (IR) imaging system. 613 is configured to capture gas IR images in the form of IR image data values/pixel values, representing infrared radiation emitted from an observed scene within 7-8.6 μm, and where the second infrared (IR) imaging system 614 is configured to capture background IR images in the form of IR image data values/pixel values, representing infrared radiation emitted from an observed scene within 9-12 μm.
Further Examples of Wavelength Bands
[0073] Table 1 shows examples of ranges of wavelength bands for different gases that may be used in embodiments described herein. So for example and as shown in the table, embodiments of a method or a device as described herein may be devised for operating on CO2 and would in this example have a high absorption wavelength band A in the range of 4,2 μm-4,6 μm and a low absorption filter B in the range of 4,4 μm-4,6 μm.
TABLE-US-00001 TABLE 1 Examples of wavelength bands for different gases High absorption Low absorption Gas Wavelength band A Wavelength band B Methane 1 3.2 μm-3.6 μm 3.4 μm-3.6 μm Methane 2 7.0 μm-9.0 μm 8.5 μm-9.0 μm CO2 4.2 μm-4.6 μm 4.4 μm-4.6 μm CO + N20 4.52 μm-4.87 μm 4.67 μm-4.87 μm Refrigerants 8.0 μm-9.0 μm 8.6 μm-9.0 μm SF6 10.3 μm-11.1 μm 10.7 μm-11.1 μm
Spatial Sensor Configuration
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[0075] The sensor 6132, comprised in the first infrared (IR) imaging system 613, is configured to capture a gas IR image simultaneously, substantially simultaneously, or with a time interval, with the sensor 6142, comprised in the second infrared (IR) imaging system 613, capturing a background IR image.
[0076] In one or more embodiments, the processor 612 is adapted to send control data to the first infrared (IR) imaging system to trigger the sensor 6132 to capture infrared radiation within the high absorption wavelength band A, and/or is adapted to send control data the second infrared (IR) imaging system to trigger the sensor 6142 to capture infrared radiation within the low absorption wavelength band B.
[0077] In one or more embodiments comprising one or more optical filters, the processor 612 is adapted to send control data to the first infrared (IR) imaging system to configure the gas optical filter 710 with a pass band equal to wavelength band A and adapted to send control data to the second infrared (IR) imaging system to configure the background optical filter 720 with a pass band equal to wavelength band B. A combination of controllable sensor and controllable optical filter are provided in one or more embodiments.
Temporal Sensor Configuration
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[0079] In one or more embodiments, the processor 612 is adapted to send control data to the first infrared (IR) imaging system to configure the captured wavelength band of the sensor 6132 to the high absorption wavelength band A and to trigger the capturing of a gas IR image at time T.sub.0, and to configure the captured wavelength band of the sensor 6132 to the low absorption wavelength band B and to trigger the capturing of a gas IR image at time T.sub.1. Typically, there is a short time lapse between the time T.sub.0 and the time T.sub.1, suitably selected to reconfigure the sensor for different wavelength bands.
[0080] In one or more embodiments comprising one or more optical filters, the processor 612 is adapted to send control data to the first infrared (IR) imaging system to configure the optical filter 710 with a pass band equal to the high absorption wavelength band A at time T.sub.0 and to configure the optical filter 710 with a pass band equal to the low absorption wavelength band B at time T.sub.1. A combination of controllable sensor and controllable optical filter are provided in one or more embodiments also in a temporal sensor configuration.
Method Embodiments
[0081] As described above one or more embodiments relate to an improved system and method of imaging quantified gas, in particular passive infrared imaging of gas occurring in a scene. The gas is imaged based on a difference in an estimated gas temperature T.sub.G and an estimated background temperature T.sub.B. Consequently, a greater difference between T.sub.G and T.sub.B will result in a greater contrast in the imaged gas in relation to background. When the estimation of T.sub.G and T.sub.B are improved, the sensitivity of the imaging system is improved and smaller amounts of gas can be detected and optionally imaged. With improved sensitivity of the imaging system, the contrast of the imaged gas is improved, e.g. in a gas-absorption-path-length image representing the length of the path of radiation from the scene background 110 through a gas occurrence in the scene.
[0082] Embodiments described herein thus increase the sensitivity of gas detection in an image, and thereby the contrast, by an improved and dynamic selection of a high absorption wavelength band A and a low absorption wavelength band B, e.g. based on previously captured gas and background IR images.
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[0084] In one or more embodiments, a method to quantify gas in a thermal imaging device 170, said method comprises a selection of: [0085] Step 810: Obtaining a gas-absorption-path-length image as a scene difference infrared image based on a gas infrared image 910 and a scene background infrared image 920 substantially depicting the same scene 110.
[0086] In one example, the gas-absorption-path-length image is obtained by retrieving it from memory 615. In yet one example, the gas-absorption-path-length image is obtained generating a gas-absorption-path-length image by a processor 612. [0087] Step 820: Generating a quantified scene difference infrared image based on said scene difference infrared image and a predefined gas-quantifying relation 180.
[0088] In one example a quantified scene difference infrared image is generated by retrieving the gas-absorption-path-length image/scene difference infrared image and a predefined gas-quantifying relation 180 from memory 615. Each pixel in the quantified scene difference infrared image is determined by applying the gas-quantifying relation 180 to each pixel in the scene difference infrared image.
[0089] In one or more embodiments, the gas-quantifying relation describes the relation between scene difference infrared image pixel values 181,900 and quantified scene difference infrared image pixel values 182 in the form of a concentration length product expressed in parts per million*meter or ppm*m, e.g. by multiplying the gas concentration by the gas-absorption path length 1601.
[0090] On one example, scene difference infrared image pixel values are generated by generating image pixel values as a selection of:
[0091] gas infrared image pixel value A.sub.row, col-background infrared image pixel value B.sub.row, col; or
[0092] background infrared image pixel value B.sub.row, col-gas infrared image pixel value A.sub.row, col,
[0093] The pixel values are for example represented by temperature values in degrees Celsius or Kelvin and the predefined gas-quantifying relation 180 is a look-up table, e.g. as depicted in relation to tables 1-4 in
[0094] In one or more embodiments, the gas-quantifying relation 180 is generated by:
[0095] measuring a first set of quantified scene difference infrared image pixel values 182 for: known gas concentration, gas-absorption path length 1601, gas temperature T.sub.G and background temperature T.sub.B; and expanding said first set to a second larger set by applying curve fitting techniques.
[0096] In one example, quantified scene difference infrared image pixel values 182 are measured using absorption spectroscopy in a controlled environment. A first set of measurement values or quantified scene difference infrared image pixel values 182 are obtained by varying the gas concentration and the gas-absorption path length 1601, e.g. by replacing sample glass vials with known gas concentration and known gas-absorption path length and monitoring the gas temperature T.sub.G and background temperature T.sub.B.
[0097] In one or more embodiments, the step 810 of obtaining a gas-absorption-path-length image further comprises and/or is preceded by: [0098] Step 803: Determining, by a processor 612, a first, high absorption wavelength band A 510 and a second, low absorption wavelength band B 520 to improve contrast in a generated gas-absorption-path-length image based on estimated image noise, a predetermined absorption spectrum of the gas 241, an estimated gas temperature TG 121 and an estimated background temperature TB 122. [0099] Step 805: Generating, by the processor 612, infrared imaging system control data to trigger the capturing, by a first infrared imaging system 613, of a gas infrared image of a scene comprising intensity of infrared radiation within high absorption wavelength band A 510 and to trigger, by a second infrared imaging system 614, the capturing of a background infrared image of the scene comprising intensity of infrared radiation within wavelength band B 520. [0100] Step 807: Generating a gas-absorption-path-length image based on the gas infrared image 910 and the background infrared image 920.
[0101] Preferably, as in one or more embodiments, high absorption wavelength band A 510 includes an absorption wavelength band G 505 from the absorption spectrum 241. Further, low absorption wavelength band B 520 may at least partially overlap high absorption wavelength band A 510. Examples of determining high absorption wavelength band A 510 and low absorption wavelength band B 520 are further described in relation to
[0102] In one example, infrared imaging system control data, comprising data indicating high absorption wavelength band A 510 and low absorption wavelength band B 520 and triggering information, is sent to a first and a second infrared imaging system 613,614. The control data is configured to control preferably the first infrared imaging system 613 to capture and return a gas infrared image of a scene comprising intensity of infrared radiation within high absorption wavelength band A 510. The control data is further configured to trigger preferably the second infrared imaging system 614 to capture a background infrared image of the scene comprising intensity of infrared radiation within low absorption wavelength band B 520. In one example the first and second infrared imaging system 613,614 are integrated in the thermal imaging device 170. In yet one example the first and second infrared imaging systems 613,614 are external to the thermal imaging device 170.
[0103] In one or more embodiments, wherein the estimated image noise comprises Noise Equivalent Temperature Difference, the quantified scene difference infrared image pixel values 182 comprise temperature values, e.g. in degrees Celsius or Kelvin. In one example, the Noise Equivalent Temperature Difference NETD is measured as Root Mean Square RMS noise, ΔU.sub.noise, which is the noise voltage measured as a Root Mean Square value of the imaging systems video channel and then converted to the corresponding temperature difference in degrees Celsius or Kelvin.
[0104] In one or more embodiments, the high absorption wavelength band A 510 is determined with a lower endpoint 5101 in the interval of [6-7.8 μm]-[8-9.6 μm]] and wherein wavelength band A 510 is determined with a higher endpoint 5502 in the interval of [8-9.6 μm].
[0105] For uncooled thermal imaging devices to be used with an acceptable image noise level, the high absorption wavelength band A and low absorption wavelength band B have to be quite broad compared to cooled cameras, as uncooled cameras have less sensitivity and a higher thermal noise contribution. As the filter regions are quite broad not only absorption of for example the gas methane is present in the filter region but also water vapor. This means that water vapor has to be quantified as well as the gas, here methane. One way to achieve this is to have an additional third, water related wavelength band C 530 determined and spectrally filtered where only water vapor absorbs the radiation, e.g. by capturing a water infrared image 1030 comprising infrared radiation within wavelength band C. This is used in order quantify water vapor and then use this measurement to generate a composite spectrum to quantify gas, for example methane. Another example to compensate for water vapor is to measure the humidity in the air and the distance from the thermal imaging device 170 to the background scene 110 and assume the humidity is the same over this whole distance. The concentration length can then be estimated as measured humidity in ppm*distance from the thermal imaging device 170 to the background scene 110, thereby calculating the concentration length of water vapor in ppm×m.
[0106] One or more embodiments, further comprises: [0107] determining, by a processor 612, a third, water related wavelength band C 530 to improve contrast in a generated gas-absorption-path-length image based on a predetermined water absorption spectrum, wherein the water related wavelength band C 530 includes at least a local maximum of the water absorption spectrum and excludes both the high absorption wavelength band A 510 and the low absorption wavelength band B 520.
[0108] Such embodiments typically further comprises: [0109] generating infrared imaging system control data to trigger the capturing of a water infrared image 1030, by a first imaging system 613 or a second imaging system 614, of the scene 110, wherein the water infrared image comprises intensity of infrared radiation within wavelength band C 530.
[0110] In these embodiments, generating a quantified scene difference infrared image is further based on the water infrared image 1030. A gas infrared image 510 in accordance with these embodiments comprises intensity of infrared radiation within the high absorption wavelength band A and the background infrared image 520 comprises intensity of infrared radiation within the low absorption wavelength band B. A water infrared image 1030 comprises intensity of infrared radiation within the wavelength band C
[0111] An example on how quantified scene difference infrared image pixel values with a gas infrared image, a background infrared image and a water infrared image are determined is further described in relation to
[0112] For visualization of a gas in a scene, a method, in accordance with one or more embodiments, further comprises: [0113] Step 830: imaging gas based on pixel values in the quantified scene difference infrared image. To enable a user to understand the information in the quantified scene difference infrared image, an image is generated to comprise a visual representation and selectively presenting it on a display 618 in the thermal imaging device or in a computing device connected to the thermal imaging device such as a tablet computer, a smartphone, a laptop or a desktop computer. The visual representation may for example be based on the quantified scene difference infrared image and a palette.
[0114] In one example, generating a visual representation comprises mapping quantified scene difference infrared image data values or pixel values of each pixel to a palette used to present the corresponding pixel displayed on a display, e.g. using grey-scale or colors selected from a color model. In yet another example of step 830, imaging gas is performed by generating a visual representation of the quantified scene difference infrared image using false coloring, wherein generating a visual representation further comprises mapping data values or pixel values in the quantified scene difference infrared image to a palette and displaying the visual representation. In yet an example, the palette comprises colors or greyscales from a predefined color model. In yet an example, wherein imaging gas further comprises displaying the display gas infrared image on a display in the thermal imaging device or on a display comprised in an external device.
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[0117] In embodiments, a gas-absorption-path-length image is generated by combining pixel values comprised in the gas infrared image 910, pixel values comprised in the background infrared image 920 and pixel values comprised in the water infrared image 1030. In yet an example the gas-absorption-path-length image pixel values are determined based on the signal difference and the gas-absorption-path-length image pixel value.sub.1, 1=A.sub.1, 1−B.sub.1, 1−C.sub.1, 1. In yet an example the gas-absorption-path-length image pixel values are determined based on the signal difference and the gas-absorption-path-length image pixel value.sub.1, 1=A.sub.1, 1−B.sub.1, 1+C.sub.1, 1. In yet an example the gas-absorption-path-length image pixel values are determined based on the signal difference and the gas-absorption-path-length image pixel value.sub.1, 1=B.sub.1, 1−A.sub.1, 1−C.sub.1, 1. In yet an example the gas-absorption-path-length image pixel values are determined based on the signal difference and the gas-absorption-path-length image pixel value.sub.1, 1=B.sub.1, 1−A.sub.1, 1+C.sub.1, 1. In yet an example the gas-absorption-path-length image pixel values are determined based on the signal difference and the gas-absorption-path-length image pixel value.sub.1, 1=A.sub.1, 1C.sub.1, 1/B.sub.1, 1. In yet an example the gas-absorption-path-length image pixel values are determined based on the signal difference and the gas-absorption-path-length image pixel value.sub.1, 1=C.sub.1, 1−A.sub.1, 1/B.sub.1, 1.
Aligning
[0118] Since the gas and background IR image 910,920 may be captured at different instances in time the thermal imaging device might be moved in a way such that the offset, direction and rotation around the optical axis differ between a gas IR image and a background IR image. Similarly, in one or more embodiments with multiple infrared imaging systems 613, 614, the orientation of optical axis of the first infrared imaging system 613 and the second infrared imaging system 614 might differ. This results in an optical phenomenon known as parallax distance error, parallax pointing error and parallax rotation error. Due to these parallax errors, the captured view of the real world scene might differ between IR images. In order to combine the gas infrared image and the background infrared image, the images must be adapted so that an adapted gas IR image and an adapted background IR image, representing the same part of the scene, is obtained, compensating for the different parallax errors and FOV size. This processing step is referred to as image registration or alignment of the first image and the second image, i.e. the process of transforming different sets of data into one coordinate system through a transform 940. Registration or alignment can be performed according to any method known to a skilled person in the art, e.g. intensity based, feature-based registration using linear or elastic transformations.
[0119] Displaying visualizing an image, IR image, quantified scene difference infrared image or gas-absorption-path-length image
[0120] As thermal images by nature are generally low contrast and noisy, the captured IR image or gas-absorption-path-length image may be subjected to various imaging processing in order to improve the interpretability of the image before displaying it to a user. Examples of such image processing is correction with IR temperature calibration data parameters, low pass filtering, registration of multiple successive IR image or gas infrared images and averaging to obtain an averaged IR image or gas infrared image or any other IR image or gas infrared image processing operation known to a person skilled in the art. As infrared radiation is not visible to the human eye there are no natural relations between the captured IR image's, quantified scene difference infrared image or gas-absorption-path-length image gas infrared image's data values of each pixel in the image and the greyscale or the colors displayed on a display. Therefore, an information visualization process referred to as false coloring or pseudo coloring is used to map image data values or pixel values of each pixel in animage, such as an IR image, quantified scene difference infrared image or gas-absorption-path-length image, to a palette used to present the corresponding pixel displayed on a display, e.g. using grey-scale or colors.
[0121] A palette is typically a finite set of color or grey-scale representations selected from a color model for the display of images or visual representations of IR images, quantified scene difference infrared image or gas-absorption-path-length image, i.e. a pre-defined palette represents a finite set of grayscale or color values of a color model displayable on a display thereby making it visible to the human eye. Mapping of image data values of each pixel in an image, such as an IR image, quantified scene difference infrared image or gas-absorption-path-length image, to a palette used to present the corresponding pixel of a visual representation of said image displayed on a display is typically performed by applying a pre-determined relation. Such a pre-determined relation typically describes a mapping from image data values or pixel values to said pre-defined palette, e.g. a palette index value with an associated color or grey-scale representation selected from a color model. The gas IR image, quantified scene difference infrared image or gas-absorption-path-length image is typically displayed to an intended user based on the image data values or pixel values of each pixel in an image, such as an IR image, quantified scene difference infrared image or gas-absorption-path-length image. Optionally IR temperature calibration data parameters, a predefined palette representing a finite set of grayscale or color values of a color model displayable on a display and a pre-determined relation describing a mapping from infrared image data values or gas-absorption-path-length image pixel values to said pre-defined palette.
Use Case Embodiments
[0122] In
[0123] A model to optimally choose filter 710,720 positions or filter tunings with regard to signal and noise affected by these filter 710,720, in accordance with one or more embodiments, is explained as follows.
[0124] The signal S is calculated by taking the exitance or measured emission of infrared radiation from the object, W.sub.obj added with the exitance or measured emission of infrared radiation from the background, W.sub.bg.
[0125] The signal S is calculated by taking the exitance from the object, W.sub.obj, added with the exitance from the background, W.sub.bg.
[0126] Where F is the F-number and is specified by the objective.
S=W.sub.bg+W.sub.obj Eq. 4
[0127] Noise
[0128] The noise of thermal cameras is often measured in NETD which stands for Noise Equivalent Temperature Difference. This is measured by the RMS noise, ΔUnoise, which is the noise voltage measured as a Root Mean Square value of the cameras video channel and then converting it to the corresponding temperature difference. NETD can then be written as follows:
[0129] Here S′T is the derivative of the signal measured by the detector at a temperature T. By taking the derivative of Eq. 4 with regard to T, S′T can be calculated. This derivative is evaluated at 30° C. since this is a common temperature for measuring NETD. Since the detector noise, ΔUnoise, in Eq. 5 is assumed to be the same with and without filter 710,720 this is regarded as a constant. The NETD is calculated by inserting a known NETD without filter and calculating S′T with τ_filter=1 to simulate a case without filtering and comparing it to NETD with the transmission of a filter. With this in mind Eq. 6 becomes:
[0130] For uncooled cameras to be used, the filter 710,720 regions have to be much broader compared to cooled cameras because uncooled cameras have less sensitivity and a higher thermal noise contribution from the optical path to the sensor/detector 6132,6142. As the filter 710,720 regions are quite broad not only absorption of gas as for example methane is present in the filter region but also water vapor. This means that water vapor has to be quantified as well as the gas, here methane. One way to achieve this is to have an additional third region spectrum filtered where only water vapor absorbs the radiation, e.g. wavelength band C 530. This is used in order quantify water vapor and then use this measurement to generate a composite spectrum to quantify methane. The other way is to measure the humidity in the air and the length to the background and assume the humidity is the same over this whole distance, and then calculate the concentration length of water vapor in ppm×m. For the calculation of signal difference between gas and no gas the temperature of gas is needed and this is assumed be the same as the temperature in the air. This means that the air temperature has to be measured as well. The input values, to calculate signal difference with gas and no gas needed, are the background temperature, the concentration length of water vapor, concentration length of methane gas and the temperature of the gas. With two different cameras that has different gain and offset values it is important to normalize the outputs so that the cameras will measure the same temperature. This is done by calibrating the cameras with the filters 710,720 and beam splitter against blackbody radiators at different known temperatures. With the measurement points of known temperatures corresponding to raw values a curve fit algorithm can be used as a function translating the raw values to temperature. Another way to quantify the gas is to practically make a calibration where different known concentrations are measured at varying distances with varying relative humidity to see how the signal in the cameras change. With these values a function can be generated that depends on signal change, distance and humidity.
Signal/Noise and Implementation
[0131] With changing cuton or lower endpoint 5101 of high absorption wavelength band A and cutoff or higher endpoint 5102 of high absorption wavelength band A, the influence of the gas can be optimized with regard to NETD and signal difference. Both the ratio between gas and no gas, and difference in signal were simulated with the motivation that theoretically the signal difference should be maximized without regard for emissivity change. Although the ratio between gas and no gas should be high because when using two cameras the normalization between the signals won't be perfect and result in a ratio difference. The chosen simulated cuton wavelengths range from 6-7.8 μm and cutoff from 8-9.6 μm with 0.2 μm steps. This is because the methane absorption peak is centered around 7.7 μm and the band pass filter 710,720 should be close to this absorption peak.
[0132]
[0133]
[0134]
[0135]
[0136] These simulations are used to decide the A filter region, or to determine wavelength band A, for the camera that should see the gas. Two different ideas are presented as one focuses on the signal difference and one on the ratio of gas vs. no gas. Since the ratio of gas vs. no gas counteracts the NETD the region was chosen to have a reasonably low NETD while the ratio is as high as possible. The region was chosen for a cuton at 7 μm and cutoff at 8.6 μm which gives a NETD of 221 mK and a ratio of 1.007 for 1000 ppmm methane.
[0137] When looking at signal differences instead of ratio, e.g. background infrared image pixel value-gas infrared image pixel value or background infrared image pixel value/gas infrared image pixel value it's clear to see from
[0138] To choose the filter wavelengths of the B region, or to determine the low absorption wavelength band B, where no or very little gas absorption should be present or where the absorption spectrum includes a local minimum the filter positions are simulated with a cutoff at 15 μm to simulate the cutoff of the camera system response and cuton ranging from 8 μm to 10.5 μm because this is where the absorption of methane will decrease to a limit where no absorption is present. This is shown in
[0139]
Quantification
[0140]
[0141] In one example, by simulating the temperature difference with spectrum containing different concentration lengths a function to determine the gas concentration length, Gas-Quantifying Relation 180, is determined. This was done with known background temperature and gas temperature. In one example, the blackbody used as background was set to 70° C. To simulate the temperature difference measured background temperature was measured with the camera and also the gas cell was measured with the camera to realize the gas temperature. For the BP filter the background temperature was measured to 79.4±0.1° C. and the gas cell was measured to 30.9±0.2° C. This gave simulated values for the temperature with regard to gas absorption.
TABLE-US-00002 TABLE 1 Simulated temperatures for different concentration-lengths for the BP filter. The table values from table 2 were plotted in MATLAB and a curve fit of the 3rd order was used to get a function that would translate the temperature values into concentration-lengths. Concentration- Simulated length temperature 1000 ppmm 73.0159° C. 5000 ppmm 70.3222° C. 10000 ppmm 68.4830° C. 20000 ppmm 66.1178° C. 30000 ppmm 64.4258° C. 60000 ppmm 60.9544° C. 120000 ppmm 56.9215° C. 200000 ppmm 53.7470° C.
[0142] Measured temperatures for different gas concentration-lengths are presented below, with their calculated concentration lengths and known concentration lengths.
TABLE-US-00003 TABLE 2 Measured temperatures with calculated concentration-lengths compared to known concentration-length for the BP filter. Known Measured concentration- Measured concentration- CL.sub.M/ length CL.sub.K temperature T length CL.sub.M CL.sub.K 5 000 ppmm 68.7° C. 9 090 ppmm 1.82 10 000 ppmm 66.7° C. 17 190 ppmm 1.72 20 000 ppmm 63.8° C. 34 270 ppmm 1.71 30 000 ppmm 61.7° C. 52 020 ppmm 1.73 60 000 ppmm 57.9° C. 102 180 ppmm 1.70 120 000 ppmm 53.7° C. 201 630 ppmm 1.68
[0143] The same procedure was done for the LP 7000 filter. For this filter the background temperature was measured to 73.5±0.1° C. and the gas cell temperature was measured to 24.3±0.1° C. This gave simulated temperature values with regard to gas absorption shown in table 4.
TABLE-US-00004 TABLE 3 Simulated temperatures for different concentration- lengths for the LP7000 filter Concentration- Simulated length temperature 1000 ppmm 73.159° C. 5000 ppmm 70.3222° C. 10000 ppmm 68.4830° C. 20000 ppmm 66.1178° C. 30000 ppmm 64.4258° C. 60000 ppmm 60.9544° C. 120000 ppmm 56.9215° C. 200000 ppmm 53.7470° C.
[0144] As for the BP filter these values are used to estimate a curve fit of the 3rd order was used to calculate the concentration length of measured temperatures.
[0145] Known concentration-length CLK Measured temperature T Measured
TABLE-US-00005 TABLE 4 Measured temperatures with calculated concentration-lengths compared to known concentration-length for the LP7000 filter. Known Measured concentration- Measured concentration- CL.sub.M/ length CL.sub.K temperature T length CL.sub.M CL.sub.K 5 000 ppmm 66.7° C. 48 630 ppmm 9.73 10 000 ppmm 66.1° C. 72 860 ppmm 7.29 20 000 ppmm 64.9° C. 156 040 ppmm 7.80 30 000 ppmm 64.5° C. 198 770 ppmm 6.63 60 000 ppmm 63.2° C. 416 940 ppmm 6.95 120 000 ppmm 61.9° C. 811 570 ppmm 6.76
[0146] As the measured values for of 416 940 ppmm and 811 570 ppmm are outside the range from the simulated concentration-length fit these may be unreliable.
Other Embodiments
[0147] The processor of described thermal imaging devices is, in accordance with one or more embodiments, configured to perform a selection of any or all of the method steps described herein that are associated with processing of captured IR images or gas-absorption-path-length images comprising image data values or pixel values, such as selection of data values/pixel values, mapping of temperature values associated with the data values/pixel values to color and/or grayscale values, assigning each pixel of a frame of IR data values a representation value from a preselected color model, e.g. based on the associated temperature value of said pixel, and other operations described herein.
[0148] In one or more embodiments, there is provided a computer-readable medium on which is stored: [0149] non-transitory information for performing a method according to any of the embodiments described herein; and/or [0150] non-transitory information configured to control a processor/processing unit to perform any of the steps or functions of embodiments described herein.
[0151] In one or more embodiments, there is provided a computer program product comprising code portions adapted to control a processor to perform any of the steps or functions of any of the embodiments described herein. Software in accordance with the present disclosure, such as program code portions and/or data, can be stored in non-transitory form on one or more machine-readable mediums. It is also contemplated that software identified herein can be implemented using one or more general purpose or specific purpose computers and/or computer systems, networked and/or otherwise.
[0152] Where applicable, one or more embodiments provided by the present disclosure can be implemented using hardware, software, or combinations of hardware and software. Also where applicable, the various hardware components and/or software components set forth herein can be combined into composite components comprising software, hardware, and/or both. Where applicable, the various hardware components and/or software components set forth herein can be separated into sub-components comprising software, hardware, or both. In addition, where applicable, it is contemplated that software components can be implemented as hardware components, and vice-versa. Where applicable, the ordering of various steps described herein can be changed, combined into composite steps, and/or separated into sub-steps to provide features described herein.
[0153] The foregoing disclosure is not intended to limit the present invention to the precise forms or particular fields of use disclosed. It is contemplated that various alternate embodiments and/or modifications to the present invention, whether explicitly described or implied herein, are possible in light of the disclosure. Accordingly, the scope of the invention is defined only by the claims.