Abstract: Embodiments relate to hue preservation post processing for highlight recovery of an input image. Intensity values for multiple color channels of a plurality of color channels of a pixel of the input image is determined using corresponding ratios of target hues for the plurality of color channels of the pixel, wherein the pixel has at least one color channel with an intensity above a predetermined threshold. A hue preserved value for a color channel of the plurality of color channels of the pixel is determined using intensity values determined for the plurality of color channels of the pixel and the target hues. A recovered version of the input image is generated by adjusting hue information of the pixel, using the hue preserved value for the channel of the plurality of color channels of the pixel.

Abstract: Occlusion of facial features may be detected and assessed in an image captured by a camera on a device. Landmark heat maps may be used to estimate the location of landmarks such as the eyes, mouth, and nose of a user's face in the captured image. An occlusion heat map may also be generated for the captured image. The occlusion heat map may include values representing the amount of occlusion in regions of the face. The estimated locations of the eyes, mouth, and nose may be used in combination with the occlusion heat map to assess occlusion scores for the landmarks. The occlusion scores for the landmarks may be used control one or more operations of the device.

Abstract: A facial recognition process operating on a device may include one or more processes that determine if a camera and/or components associated with the camera are obstructed by an object (e.g., a user's hand or fingers). Obstruction of the device may be assessed using flood infrared illumination images when a user's face is not able to be detected by a face detection process operating on the device. Obstruction of the device may also be assessed using a pattern detection process that operates after the user's face is detected by the face detection process. When obstruction of the device is detected, the device may provide a notification to the user that the device (e.g., the camera and/or an illuminator) is obstructed and that the obstruction should be removed for the facial recognition process to operate correctly.

Abstract: Embodiments relate to hue preservation post processing for highlight recovery of an input image. Intensity values for multiple color channels of a plurality of color channels of a pixel of the input image is determined using corresponding ratios of target hues for the plurality of color channels of the pixel, wherein the pixel has at least one color channel with an intensity above a predetermined threshold. A hue preserved value for a color channel of the plurality of color channels of the pixel is determined using intensity values determined for the plurality of color channels of the pixel and the target hues. A recovered version of the input image is generated by adjusting hue information of the pixel, using the hue preserved value for the channel of the plurality of color channels of the pixel.

Abstract: Embodiments relate to hue preservation post processing for highlight recovery of an input image. Intensity values for multiple color channels of a plurality of color channels of a pixel of the input image is determined using corresponding ratios of target hues for the plurality of color channels of the pixel, wherein the pixel has at least one color channel with an intensity above a predetermined threshold. A hue preserved value for a color channel of the plurality of color channels of the pixel is determined using intensity values determined for the plurality of color channels of the pixel and the target hues. A recovered version of the input image is generated by adjusting hue information of the pixel, using the hue preserved value for the channel of the plurality of color channels of the pixel.

Abstract: Occlusion of facial features may be detected and assessed in an image captured by a camera on a device. Landmark heat maps may be used to estimate the location of landmarks such as the eyes, mouth, and nose of a user's face in the captured image. An occlusion heat map may also be generated for the captured image. The occlusion heat map may include values representing the amount of occlusion in regions of the face. The estimated locations of the eyes, mouth, and nose may be used in combination with the occlusion heat map to assess occlusion scores for the landmarks. The occlusion scores for the landmarks may be used control one or more operations of the device.

Abstract: Occlusion of facial features may be detected and assessed in an image captured by a camera on a device. Landmark heat maps may be used to estimate the location of landmarks such as the eyes, mouth, and nose of a user's face in the captured image. An occlusion heat map may also be generated for the captured image. The occlusion heat map may include values representing the amount of occlusion in regions of the face. The estimated locations of the eyes, mouth, and nose may be used in combination with the occlusion heat map to assess occlusion scores for the landmarks. The occlusion scores for the landmarks may be used control one or more operations of the device.

Abstract: Embodiments relate to generation of hue maps for highlight recovery of an input image. An image having a plurality of color channels is obtained at a first resolution lower than a resolution of the input image. A hue for each color channel for each pixel is determined, using a pixel value for that color channel and pixel values for the plurality of color channels in the first image. Weights are determined for each pixel for each color channel, based on hues for the pixel and pixel values for the pixel in the first image. A plurality of candidate hue maps are generated, based on the weights and pixel values in the first image in a patch surrounding the pixel for the plurality of color channels.

Abstract: A facial recognition process operating on a device may include one or more processes that determine if a camera and/or components associated with the camera are obstructed by an object (e.g., a user's hand or fingers). Obstruction of the device may be assessed using flood infrared illumination images when a user's face is not able to be detected by a face detection process operating on the device. Obstruction of the device may also be assessed using a pattern detection process that operates after the user's face is detected by the face detection process. When obstruction of the device is detected, the device may provide a notification to the user that the device (e.g., the camera and/or an illuminator) is obstructed and that the obstruction should be removed for the facial recognition process to operate correctly.

Abstract: Embodiments relate to hue preservation post processing for highlight recovery of an input image. Intensity values for multiple color channels of a plurality of color channels of a pixel of the input image is determined using corresponding ratios of target hues for the plurality of color channels of the pixel, wherein the pixel has at least one color channel with an intensity above a predetermined threshold. A hue preserved value for a color channel of the plurality of color channels of the pixel is determined using intensity values determined for the plurality of color channels of the pixel and the target hues. A recovered version of the input image is generated by adjusting hue information of the pixel, using the hue preserved value for the channel of the plurality of color channels of the pixel.

Abstract: Embodiments relate to generation of hue maps for highlight recovery of an input image. An image having a plurality of color channels is obtained at a first resolution lower than a resolution of the input image. A hue for each color channel for each pixel is determined, using a pixel value for that color channel and pixel values for the plurality of color channels in the first image. Weights are determined for each pixel for each color channel, based on hues for the pixel and pixel values for the pixel in the first image. A plurality of candidate hue maps are generated, based on the weights and pixel values in the first image in a patch surrounding the pixel for the plurality of color channels.

Abstract: Occlusion of facial features may be detected and assessed in an image captured by a camera on a device. Landmark heat maps may be used to estimate the location of landmarks such as the eyes, mouth, and nose of a user's face in the captured image. An occlusion heat map may also be generated for the captured image. The occlusion heat map may include values representing the amount of occlusion in regions of the face. The estimated locations of the eyes, mouth, and nose may be used in combination with the occlusion heat map to assess occlusion scores for the landmarks. The occlusion scores for the landmarks may be used control one or more operations of the device.

Abstract: This disclosure pertains to systems, methods, and computer readable media for performing lens shading correction (LSC) operations that modulate gains based on scene lux level and lens focus distance. These gains compensate for both color lens shading (i.e., the deviation between R, G, and B channels) and vignetting (i.e., the drop off in pixel intensity around the edges of an image). As scene illuminance increases, the sensor captures more signal from the actual scene, and the lens shading effects begin to appear. To deal with the situation, the lens shading gains are configured to adaptively ‘scale down’ when scene lux approaches zero and ‘scale up’ when scene lux changes from near zero to become larger. The lens shading gain may also be modulated based on the focus distance. For optical systems without zoom, the inventors have discovered that the amount of lens shading fall off changes as focus distance changes.

Abstract: Embodiments of the present disclosure relate to highlight recovery of a high-resolution image using a single low-resolution image captured at a lower exposure. An example apparatus includes a hue target circuit that receives an input image at a high-resolution including at least one pixel with a clipped color channel. For example, the input image is a Blue sky image with a pixel having clipped Blue channel. The hue target circuit also receives a set of candidate hue maps having a pixel resolution lower than the high-resolution of the input image. The hue target circuit generates a target hue value for the at least one pixel using the pixel information of the set of candidate hue maps. The apparatus also includes a hue recovery circuit that generates a recovered version of the input image by adjusting hue information of the clipped color channel based on the generated target hue.

Abstract: Embodiments of the present disclosure relate to highlight recovery of a high-resolution image using a single low-resolution image captured at a lower exposure. An example apparatus includes a hue target circuit that receives an input image at a high-resolution including at least one pixel with a clipped color channel. For example, the input image is a Blue sky image with a pixel having clipped Blue channel. The hue target circuit also receives a set of candidate hue maps having a pixel resolution lower than the high-resolution of the input image. The hue target circuit generates a target hue value for the at least one pixel using the pixel information of the set of candidate hue maps. The apparatus also includes a hue recovery circuit that generates a recovered version of the input image by adjusting hue information of the clipped color channel based on the generated target hue.

Abstract: This disclosure pertains to systems, methods, and computer readable media for performing lens shading correction (LSC) operations that modulate gains based on scene lux level and lens focus distance. These gains compensate for both color lens shading (i.e., the deviation between R, G, and B channels) and vignetting (i.e., the drop off in pixel intensity around the edges of an image). As scene illuminance increases, the sensor captures more signal from the actual scene, and the lens shading effects begin to appear. To deal with the situation, the lens shading gains are configured to adaptively ‘scale down’ when scene lux approaches zero and ‘scale up’ when scene lux changes from near zero to become larger. The lens shading gain may also be modulated based on the focus distance. For optical systems without zoom, the inventors have discovered that the amount of lens shading fall off changes as focus distance changes.

Abstract: This disclosure pertains to systems, methods, and computer readable media for performing lens shading correction (LSC) operations that modulate gains based on scene lux level and lens focus distance. These gains compensate for both color lens shading (i.e., the deviation between R, G, and B channels) and vignetting (i.e., the drop off in pixel intensity around the edges of an image). As scene illuminance increases, the sensor captures more signal from the actual scene, and the lens shading effects begin to appear. To deal with the situation, the lens shading gains are configured to adaptively ‘scale down’ when scene lux approaches zero and ‘scale up’ when scene lux changes from near zero to become larger. The lens shading gain may also be modulated based on the focus distance. For optical systems without zoom, the inventors have discovered that the amount of lens shading fall off changes as focus distance changes.

Abstract: Methods and systems to improve the operation of graphic's system are described. In general, techniques are disclosed for compensating for an image sensor's non-zero black-level output. More particularly, a image sensor noise model may be used to offset an image's signal prior to clipping so that the image's dark signal exhibits a linear or near linear mean characteristic after clipping. In one implementation the noise model may be based on calibration or characterization of the image sensor prior to image capture. In another implementation the noise model may be based on an evaluation of the image itself during image capture operations. In yet another implementation the noise model may be based on analysis of an image post-capture (e.g., hours, days, . . . after initial image capture).

Abstract: An image processing pipeline may account for clipped pixels in auto focus statistics. Generating auto focus statistics may include evaluating a neighborhood of pixels with respect to a given pixel in a stream of pixels for an image. If a clipped pixel is identified within the neighborhood of pixels then the evaluation of the given pixel may be excluded from an auto focus statistic. The image processing pipeline may also provide auto focus statistics that do not exclude clipped pixels. A luminance edge detection value may, in some embodiments, be generated by applying an IIR filter to the given pixel in a stream of pixels to band-pass filter the given pixel before including the band-pass filtered pixel in the generation of the luminance edge detection value.

Abstract: An image processing pipeline may account for clipped pixels in auto focus statistics. Generating auto focus statistics may include evaluating a neighborhood of pixels with respect to a given pixel in a stream of pixels for an image. If a clipped pixel is identified within the neighborhood of pixels then the evaluation of the given pixel may be excluded from an auto focus statistic. The image processing pipeline may also provide auto focus statistics that do not exclude clipped pixels. A luminance edge detection value may, in some embodiments, be generated by applying an IIR filter to the given pixel in a stream of pixels to band-pass filter the given pixel before including the band-pass filtered pixel in the generation of the luminance edge detection value.