A system for obtaining color imagery using SPADs includes a SPAD array that has a plurality of SPAD pixels. Each of the plurality of SPAD pixels includes a respective color filter positioned thereover. The system is configurable to capture an image frame using the SPAD array and generate a filtered image by performing a temporal filtering operation using the image frame and at least one preceding image frame. The at least one preceding image frame is captured by the SPAD array at a timepoint that temporally precedes a timepoint associated with the image frame. The system is also configurable to, after performing the temporal filtering operation, generate a color image by demosaicing the filtered image.

In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a number of first filter types. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data based on a portion of the first image data associated with the filter type in common.

The technology disclosed relates to classification of process cycle images to predict success or failure of process cycles. The technology disclosed includes capturing and processing images of sections arranged on an image generating chip in genotyping process. Image description features of production cycle images are created and given as input to classifiers. A trained classifier separates successful production images from unsuccessful or failed production images. The failed production images are further classified by a trained root cause classifier into various categories of failure.

There is provided an analyzer apparatus capable of generating crisp scanned images. In the analyzer apparatus, a sample is scanned with a probe such that a first signal and a second signal are emitted from the sample. The analyzer apparatus comprises: a first detector for detecting the first signal and producing a first detector signal; a second detector for detecting the second signal and producing a second detector signal; and an image processing unit operating (i) to produce a first scanned image and a second scanned image from the first detector signal and the second detector signal, respectively, (ii) to create a filter based on the second scanned image having a higher signal-to-noise ratio than that of the first scanned image, and (iii) to apply the filter to the first scanned image.

Systems and methods for hybrid depth regularization in accordance with various embodiments of the invention are disclosed. In one embodiment of the invention, a depth sensing system comprises a plurality of cameras; a processor; and a memory containing an image processing application. The image processing application may direct the processor to obtain image data for a plurality of images from multiple viewpoints, the image data comprising a reference image and at least one alternate view image; generate a raw depth map using a first depth estimation process, and a confidence map; and generate a regularized depth map. The regularized depth map may be generated by computing a secondary depth map using a second different depth estimation process; and computing a composite depth map by selecting depth estimates from the raw depth map and the secondary depth map based on the confidence map.

An image detection obtains original image. The original image is corrected to obtain a corrected image. Median filtering is performed on the corrected image to obtain a filtered image. A contrast of the filtered image is adjusted to obtain an adjusted image. Bilateral filtering is performed on the adjusted image to obtain an enhanced image. Defects in the enhanced image is detected. The method can detect defects in images accurately and efficiently.

A system includes an image sensor, an imaging pipeline, and a display device. The image sensor is configured to capture a first frame of pixel data. The imaging pipeline is coupled to the image sensor to receive the first frame of pixel data. The imaging pipeline includes an adaptive noise filter. The adaptive noise filter is configured to filter a pixel based on noise in the pixel. The imaging pipeline is configured to output a second frame of pixel data. The second frame of pixel data includes pixels filtered by the adaptive noise filter. The display device is coupled to the imaging pipeline to receive the second frame of pixel data. The display device is configured to display the second frame of pixel data.

A pupil tracking method includes: retrieving an external eye image of a subject, wherein the external eye image includes a pupil of the subject; performing an image preprocessing on the external eye image, wherein the image preprocessing includes performing a binary conversion on the external eye image to obtain a binary image; finding out a contour boundary of each feature in the binary image, and finding out a pupil feature based on a variance of a distance from the contour boundary of each feature to a corresponding reference point; fitting the contour boundary of the pupil feature by a boundary fitting method to find a center coordinate of the pupil feature. The abovementioned pupil tracking method can track the pupil of the subject's eyeball without using a stereo camera. An ophthalmology inspection device using the abovementioned pupil tracking method is also disclosed.

An image processing method and device, and a computer-readable storage medium are disclosed. The method includes: performing a channel expansion process on the input image to obtain a first intermediate image; performing a channel decomposition process for multiple times based on the first intermediate image, wherein each time of channel decomposition process includes: decomposing an image to be processed into a first decomposition image and a second decomposition image; concatenating first decomposition images generated in each time of channel decomposition process and second decomposition image generated in the last time of channel decomposition process to obtain a concatenated image; performing a post-processing process on the concatenated image to obtain a second intermediate image; and fusing the second intermediate image with the input image to obtain the first output image.

A system for obtaining color imagery using SPADs includes a SPAD array that has a plurality of SPAD pixels. Each of the plurality of SPAD pixels includes a respective color filter positioned thereover. The system is configurable to capture an image frame using the SPAD array and generate a filtered image by performing a temporal filtering operation using the image frame and at least one preceding image frame. The at least one preceding image frame is captured by the SPAD array at a timepoint that temporally precedes a timepoint associated with the image frame. The system is also configurable to, after performing the temporal filtering operation, generate a color image by demosaicing the filtered image.