Described are systems, methods, and apparatus for generating motion extracted images having a high dynamic range (HDR) based on image data obtained from one or more image sensors at different times. The implementations described herein may be used with a single image sensor or camera that obtains images at different exposures sequentially in time. The images may be processed to detect an object moving within the field of view and pixel information corresponding to that moving object extracted. The non-extracted image data may then be combined to produce a motion extracted HDR image that is substantially devoid of the moving object.

Methods, systems, apparatuses, and computer-readable storage mediums described herein are configured to fuse image frames captured by a camera to generate an image frame having high dynamic range and reduced amount of noise. For instance, after a shutter button of the camera is activated, one or more history image frames captured during a preview mode of the camera (e.g., before the shutter button is activated) are compared to a highlight recovery frame captured after the shutter button is activated to determine a level of similarity therebetween. The history image frame(s) may be captured with a first exposure value, and the highlight recovery frame may be captured with a second exposure value that is different than the first exposure value. History image frame(s) that are determined to be relatively similar to the highlight recovery frame are combined with the highlight recovery frame to generate the image frame having high dynamic range.

Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Devices, methods, and non-transitory program storage devices are disclosed herein to provide improved image processing, the techniques comprising: obtaining an input image and target image data, and then calculating derivatives for the target image data using a regularized derivative kernel operator. In some embodiments, the regularized operator may comprise the following operator: [1 (1+)], wherein may be a controllable system parameter and preferably is independent of the particular type of image processing being applied to the image. In some embodiments, the techniques may find look-up table (LUT) mappings or analytical functions to approximate the derivative structure of the target image data. Finally, the techniques disclosed herein may generate an output image from the input image based on attempting to closely approximate the calculated derivatives for the target image data. In preferred embodiments, by controlling the mapping, e.g., using regularization techniques, halos and other image artifacts may be ameliorated.

An imaging system includes an image sensor and an image signal processor (ISP). The image sensor generates image data including a set of pixel values. The ISP defines a first subset of pixel values from the set of pixel values. The first subset of pixel values corresponds to at least one region of interest. The ISP defines a second subset of pixel values that is complementary to the first subset of pixel values. The ISP generates a first sub-image based on the second subset of pixel values. The ISP processes the first subset of pixel values to generate a second sub-image. Processing the first subset of pixel values includes at least one of changing a color of one or more pixel values from the first subset of pixel values and scaling the first subset of pixel values. The ISP merges the first and second sub-images to generate an output image.

The present invention proposes a method for rapidly dehazing an underground pipeline image based on dark channel prior (DCP). The method includes: preprocessing a hazy underground pipeline image to obtain a dark channel image corresponding to the hazy image; average-filtering the obtained dark channel image to estimate an image transmittance; compensating an offset value for an average filtering result to obtain a rough estimate of the transmittance; using a pixel value of the original image and an average-filtered image to estimate a global atmospheric light value; and using a physical restoration model to restore a dehazed image. The method of the present invention realizes the timeliness of the algorithm while ensuring the dehazing effect, and is suitable for scientific fields such as video monitoring of underground pipeline environment and identification of underground pipeline defects.

An image capturing apparatus including: an imaging sensor and a processor configured to set a first exposure time and a second exposure time obtained by dividing the first exposure time by an integer m where m is an integer equal to or larger than 2; control the imaging sensor to capture frames successively by repeatedly performing exposure including at least exposure for one frame having the first exposure time and exposure for m frames having the second exposure time as one set; acquire image data of each frame from the imaging sensor; generate image data of an average frame that is an average of pieces of image data of the m frames having the second exposure time in the one set; and generate a composite frame for recording or displaying a motion picture of an extended dynamic range according to image data of the one frame having the first exposure time and the image data of the average frame.

The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize context-aware sensors and multi-dimensional gesture inputs across a digital image to generate enhanced digital images. In particular, the disclosed systems can provide a dynamic sensor over a digital image within a digital enhancement user interface (e.g., a user interface without visual elements for modifying parameter values). In response to selection of a sensor location, the disclosed systems can determine one or more digital image features at the sensor location. Based on these features, the disclosed systems can select and map parameters to movement directions. Moreover, the disclosed systems can identify a user input gesture comprising movements in one or more directions across the digital image. Based on the movements and the one or more features at the sensor location, the disclosed systems can modify parameter values and generate an enhanced digital image.

In an embodiment, a method of emulating light sensitivity of a target includes, for each of at least some frames of a video recording, receiving an image. The method also includes accessing image metadata associated with the image. The method also includes discovering, from the image metadata, information related to an exposure setting and a gain value used by a camera in capture of the image. The method also includes deriving, from stored camera metadata for the camera, information related to a luminous flux associated with the exposure setting and the gain value used by the camera in the capture of the image. The method also includes determining an adjusted gain value corresponding to a target light sensitivity using the derived information related to the luminous flux. The method also includes generating an adjusted image using the adjusted gain value.

An image display apparatus includes a display, an input unit configured to receive input data including an input image in which a first dynamic range is defined and including information relating to luminance of the input image, and at least one processor or circuit for executing tasks of converting the first dynamic range into a second dynamic range having a maximum luminance lower than that of the first dynamic range, acquiring a user set maximum luminance of the second dynamic range, acquiring a maximum display luminance when the display unit displays the maximum luminance of the second dynamic range under a display condition set for the display unit, and generating a setting screen for a user setting. The setting screen displays information indicating a relative relation among the information relating to luminance acquired from the data, the user set maximum luminance and the maximum display luminance.