Abstract: A method of compression includes compressing a captured image from a first bit-depth at which it was captured to a second bit-depth that is less than the first bit-depth. The compression comprises applying, according to a power curve, a first compression amount to a first region of the captured image having a first pixel value; and applying, according to the power curve, a second compression amount to a second part of the captured image having a higher second pixel value, wherein the first compression amount is lower than the second compression amount.

Abstract: Apparatuses, systems, and techniques to process luminance and/or radiance values of one or more images from one or more cameras using one or more neural networks to perform a machine vision task. In at least one embodiment, one or more neural networks determine detection difficulty levels of objects within the one or more images and performs a machine vision task based on the determined detection difficulty levels of objects within images associated with that ask.

Abstract: A method of decompression includes decompressing a compressed image according to a power curve to generate a partially decompressed image, wherein the compressed image is decompressed from a second bit depth that is lower than a first bit-depth at which the image was generated.

Abstract: Devices, methods, and systems are provided. In one example, a device is described to include circuitry that collects data received from a data source, references a descriptor that describes a data reformat operation to perform on the data received from the data source, reformats the data received from the data source according to the data reformat operation, and provides the reformatted data to the data target via the second device interface.

Abstract: A system, such as for use in an automobile, is configured to process image data that includes infrared values and visible light values (e.g., data generated by a red, green, blue, infrared (RGB-IR) sensor). The system determines how to blend IR data and visible light data together to generate optimal images according to current light levels. In embodiments, the system computes a scene detection value for the image data based on a comparison between the infrared values and the visible light values. The system can then determine an amount of infrared correction, a color correction factor, a color saturation factor, etc. to apply to the image data. The system then transforms the image data based on the amount of infrared correction, the color correction factor, the color saturation factor, etc. The transformed image data includes more information for low light scenes than is traditionally available, and thus produces higher quality images in embodiments.

Abstract: Apparatuses, systems, and techniques for reliable image data capture are disclosed herein. A system includes a sensor configured to receive light reflected off one or more objects in an environment. The sensor includes a first set of sensor pixels configured to detect a portion of the received light having wavelengths in the visible light spectrum. The sensor further includes a second set of sensor pixels configured to detect an additional portion of the received light having wavelengths in an infrared spectrum. The system further includes a filter component configured to reduce an intensity of the portion of the received light detected by the first set of sensor pixels while maintaining at least a minimum intensity of the additional portion of the received light detected by the second set of sensor pixels.

Abstract: In one embodiment, a system receives pixel data from a pair of regions of an image generated by an imaging device, the pair of regions includes a first region and a second region, where the first region includes a first plurality of pixels and the second region includes a second plurality of pixels. The system determines a plurality of pixel pairs, where a pixel pair includes a first pixel from the first plurality of pixels and a second pixel from the second plurality of pixels. The system calculates a plurality of contrasts based on the plurality of pixel pairs. The system determines a contrast distribution based on the plurality of contrasts. The system calculates a value representative of a capability of the imaging device to detect contrast based on the contrast distribution. The system determines a reduction in contrast detectability of the imaging device based on the value.

Abstract: In one embodiment, a system determines pixel data from a pair of regions of an image generated by an imaging device, the pair of regions includes a first region and a second region, where the first region includes a first plurality of pixels and the second region includes a second plurality of pixels. The system determines a plurality of pixel pairs of the image, where a pixel pair includes a first pixel from the first plurality of pixels and a second pixel from the second plurality of pixels. The system calculates a plurality of contrasts based on the plurality of pixel pairs, where a contrast is calculated between the first pixel and the second pixel. The system determines a contrast distribution based on the plurality of contrasts. The system calculates a value representative of a capability of the imaging device to detect contrast based on the contrast distribution.

Abstract: In one embodiment, a system receives pixel data from a pair of regions of an image generated by an imaging device, the pair of regions includes a first region and a second region, where the first region includes a first plurality of pixels and the second region includes a second plurality of pixels. The system determines a plurality of pixel pairs, where a pixel pair includes a first pixel from the first plurality of pixels and a second pixel from the second plurality of pixels. The system calculates a plurality of contrasts based on the plurality of pixel pairs. The system determines a contrast distribution based on the plurality of contrasts. The system calculates a value representative of a capability of the imaging device to detect contrast based on the contrast distribution. The system determines a reduction in contrast detectability of the imaging device based on the value.

Abstract: A method of decompression includes decompressing a compressed image according to a power curve to generate a partially decompressed image, wherein the compressed image is decompressed from a second bit depth that is lower than a first bit-depth at which the image was generated.

Abstract: Apparatuses, systems, and techniques to receive, at one or more processors associated with an image signal processing (ISP) pipeline for a camera, an image generated using an image sensor of the camera, wherein the image comprises a plurality of channels associated with color information of the image; process, by the one or more processors, the plurality of channels of the image to generate a plurality of luminance and/or radiance values; generate, by the one or more processors, an updated version of the image using the plurality of luminance and/or radiance values; and output the updated version of the image.

Abstract: Apparatuses, systems, and techniques to receive, at one or more processor associated with an image signal processing (ISP) pipeline, a compressed image generated by an image sensor, wherein the compressed image is captured at a first bit-depth associated with the image sensor and is compressed to a second bit-depth that is lower than the first bit-depth, and wherein the ISP is associated with a third bit-depth that is lower than the first bit-depth and higher than the second bit-depth; and decompress the compressed image according to a power curve to generate a partially decompressed image having the third bit-depth, wherein a plurality of regions of the partially decompressed image are decompressed at separate decompression amounts based on a corresponding pixel value of each region of the plurality of regions.

Abstract: Apparatuses, systems, and techniques to receive, at one or more processor associated with an image signal processing (ISP) pipeline, a compressed image generated by an image sensor, wherein the compressed image is captured at a first bit-depth associated with the image sensor and is compressed to a second bit-depth that is lower than the first bit-depth, and wherein the ISP is associated with a third bit-depth that is lower than the first bit-depth and higher than the second bit-depth; and decompress the compressed image according to a power curve to generate a partially decompressed image having the third bit-depth, wherein a plurality of regions of the partially decompressed image are decompressed at separate decompression amounts based on a corresponding pixel value of each region of the plurality of regions.

Abstract: In various examples, apparatuses, systems, and techniques to perform offline image signal processing of source image data to generate target image data. In at least one embodiment, data collection using exposure and calibration setting of an image sensor is performed to generate source image data, which is then processed by using offline image signal processing to generate target data.

Abstract: In one embodiment, a system receives pixel data from a pair of regions of an image generated by an imaging device, the pair of regions includes a first region and a second region, where the first region includes a first plurality of pixels and the second region includes a second plurality of pixels. The system determines a plurality of pixel pairs, where a pixel pair includes a first pixel from the first plurality of pixels and a second pixel from the second plurality of pixels. The system calculates a plurality of contrasts based on the plurality of pixel pairs. The system determines a contrast distribution based on the plurality of contrasts. The system calculates a value representative of a capability of the imaging device to detect contrast based on the contrast distribution. The system determines a reduction in contrast detectability of the imaging device based on the value.

Abstract: In one embodiment, a system determines pixel data from a pair of regions of an image generated by an imaging device, the pair of regions includes a first region and a second region, where the first region includes a first plurality of pixels and the second region includes a second plurality of pixels. The system determines a plurality of pixel pairs of the image, where a pixel pair includes a first pixel from the first plurality of pixels and a second pixel from the second plurality of pixels. The system calculates a plurality of contrasts based on the plurality of pixel pairs, where a contrast is calculated between the first pixel and the second pixel. The system determines a contrast distribution based on the plurality of contrasts. The system calculates a value representative of a capability of the imaging device to detect contrast based on the contrast distribution.

Abstract: Dynamic white point management techniques include determining a white point of ambient light proximate to a display. A color profile adjustment is determined based upon the determined white point and intensity of the ambient light. The image color space is transformed to a display color space for rendering on the display based on the determined adjusted to the color profile.

Abstract: Embodiments of the present invention are directed to methods and systems for robust weighting of gray patches in automatic white balancing in an image-capture device by utilizing kernel density estimation techniques with dynamically variable bandwidth to determine the probability density of samples to create an initial estimate, then verifying the initial gray point estimate to account for outliers. In one embodiment, given a set of image data, an initial gray point estimate in a color space is determined for the set of image data. The initial estimate is then refined by weighting the sub-population with the greatest probability of being gray. A final evaluation that includes a further comparison to pre-programmed constraints determines a final estimate, which can still be further tuned according to user preferences by adjusting color biases. The resulting final gray point estimate provides greater stability, and greatly improved accuracy over traditional techniques and solutions.

Abstract: Embodiments of the present invention are directed to methods and systems for robust weighting of gray patches in automatic white balancing in an image-capture device by utilizing kernel density estimation techniques with dynamically variable bandwidth to determine the probability density of samples to create an initial estimate, then verifying the initial gray point estimate to account for outliers. In one embodiment, given a set of image data, an initial gray point estimate in a color space is determined for the set of image data. The initial estimate is then refined by weighting the sub-population with the greatest probability of being gray. A final evaluation that includes a further comparison to pre-programmed constraints determines a final estimate, which can still be further tuned according to user preferences by adjusting color biases. The resulting final gray point estimate provides greater stability, and greatly improved accuracy over traditional techniques and solutions.