Abstract: Image signal processing includes obtaining two or more image signals from a first hyper-hemispherical image sensor, where each of the two or more image signals has a different exposure and obtaining two or more image signals from a second hyper-hemispherical image sensor, where each of the two or more image signals has a different exposure. Image signal processing includes generating an exposure compensated image based on a gain value applied to an exposure level of a first image and a gain value applied to an exposure level of a second image. Image signal processing further includes performing high dynamic range (HDR) processing on the exposure compensated image. The HDR processing may be performed on a high a frequency portion of the exposure compensated image.

Abstract: An image capture apparatus may include an image sensor, a motion sensor, and an auto-exposure unit. The auto-exposure unit may obtain an input image captured during an exposure interval and corresponding motion data indicating motion of the image capture apparatus during the exposure interval. The auto-exposure unit may obtain image information-amount data for the input image. The auto-exposure unit may obtain derivative information-amount data based on the information-amount data and a candidate exposure adjustment. The auto-exposure unit may obtain an information-amount maximizing exposure interval based on the information-amount data and the derivative information-amount data. The image capture apparats may control the image sensor to obtain a subsequent input image signal representing a subsequent input image captured during the information-amount maximizing exposure interval, and output or store information representing the subsequent input image.

Abstract: Flare compensation includes receiving a first image and a second image; converting the first and the second images from an RGB domain to a YUV domain; obtaining an intensity differences profile along a stitch line between the first and the second images, where the intensity differences profile is obtained for the Y component; obtaining a dark corner intensity differences profile between the first and the second images based on a relative illumination of an area outside a first image circle of the first image and a second image circle of the second image, where the dark corner intensity differences profile is obtained for the Y component; obtaining a flare profile using the intensity differences profile and the dark corner intensity differences profile; converting the flare profile of the Y component to an RGB flare profile; and modifying one of the first or second images based on the RGB flare profile.

Abstract: Multiple lookup tables (LUTs) storing different numbers of control point values are used to process pixels within different blocks of an image, such as after image processing using tone mapping and/or tone control, and/or to collect histogram information or implement 3D LUTs. First control point values stored within a first LUT are applied against pixels of a given block of an image to produce a distorted image block. Second control point values stored within a second lookup table are applied against a pixel of the distorted image block to produce a processed pixel. The second LUT is one of a plurality of second LUTs and stores fewer values than the first LUT. A processed image is produced using the processed pixel. The processed image is then output for further processing or display.

Abstract: Systems and methods are disclosed for high dynamic rate processing based on angular rate measurements. For example, methods may include receiving a short exposure image that was captured using an image sensor; receiving a long exposure image that was captured using the image sensor; receiving an angular rate measurement captured using an angular rate sensor attached to the image sensor during exposure of the long exposure image; determining, based on the angular rate measurement, whether to apply high dynamic range processing to an image portion of the short exposure image and the long exposure image; and responsive to a determination not to apply high dynamic range processing to the image portion, selecting the image portion of the short exposure image for use as the image portion of an output image and discard the image portion of the long exposure image.

Abstract: Image analysis and processing may include a first sensor readout unit receiving first Bayer format image data corresponding to a first input image, a second sensor readout unit receiving second Bayer format image data corresponding to a second input image, a first Bayer-to-RGB unit obtaining first RGB format image data based on the first Bayer format image data, a second Bayer-to-RGB unit obtaining second RGB format image data based on the second Bayer format image data, a high dynamic range unit configured obtaining high dynamic range image data based on a combination of the first RGB format image data and the second RGB format image data, an RGB-to-YUV unit obtaining YUV format image data based on the high dynamic range image data, and a three-dimensional noise reduction unit obtaining processed image data based on the YUV format image data.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a current image of a sequence of images from an image sensor; combining the current image with a recirculated image to obtain a noise reduced image, where the recirculated image is based on one or more previous images of the sequence of images from the image sensor; determining a noise map for the noise reduced image, where the noise map is determined based on estimates of noise levels for pixels in the current image, a noise map for the recirculated image, and a set of mixing weights; recirculating the noise map with the noise reduced image to combine the noise reduced image with a next image of the sequence of images from the image sensor; and storing, displaying, or transmitting an output image that is based on the noise reduced image.

Abstract: An image capture apparatus may include an image sensor, a motion sensor, and an auto-exposure unit. The auto-exposure unit may obtain an input image captured during an exposure interval and corresponding motion data indicating motion of the image capture apparatus during the exposure interval. The auto-exposure unit may obtain image information-amount data for the input image. The auto-exposure unit may obtain derivative information-amount data based on the information-amount data and a candidate exposure adjustment. The auto-exposure unit may obtain an information-amount maximizing exposure interval based on the information-amount data and the derivative information-amount data. The image capture apparats may control the image sensor to obtain a subsequent input image signal representing a subsequent input image captured during the information-amount maximizing exposure interval, and output or store information representing the subsequent input image.

Abstract: A system accesses an image with each pixel of the image having luminance values each representative of a color component of the pixel. The system generates a first histogram for aggregate luminance values of the image, and accesses a target histogram for the image representative of a desired global image contrast. The system computes a transfer function based on the first histogram and the target histogram such that when the transfer function is applied, a histogram of the modified aggregate luminance values is within a threshold similarity of the target histogram. The system modifies the image by applying the transfer function to the luminance values of the image to produce a tone mapped image, and outputs the modified image.

Abstract: Image analysis and processing may include a first sensor readout unit configured to receive first Bayer format image data, a second sensor readout unit configured to receive second Bayer format image data, a first Bayer-to-RGB unit configured to obtain first RGB format image data based on the first Bayer format image data, a second Bayer-to-RGB unit configured to obtain second RGB format image data based on the second Bayer format image data, a high dynamic range unit configured to obtain high dynamic range image data based on a combination of the first RGB format image data and the second RGB format image data, an RGB-to-YUV unit configured to obtain YUV format image data based on the high dynamic range image data, and a three-dimensional noise reduction unit configured to obtain noise reduced image data based on the YUV format image data.

Abstract: Flare compensation includes obtaining a first input frame, which includes lens flare, and a second input frame; obtaining a stitch line between the first input frame and the second input frame; obtaining, for the first input frame, a first intensity profile; obtaining, for the second input frame, a second intensity profile; obtaining an intensity differences profile; obtaining a first dark corner profile based on a first illumination of a first area outside a first image circle of the first input frame; obtaining a second dark corner profile based on a second illumination of a second area outside a second image circle of the second input frame; obtaining a dark corner difference profile; calculating a flare model; obtaining a flare mask; and correcting the first input frame by subtracting the flare mask from the first input frame.

Abstract: A face located along a stitch line in a spherical image is detected by rendering views of regions of the spherical image along the stitch line. The spherical image may be produced by combining first and second images. A first view of a projection of the spherical image is rendered. A scaling factor for rendering a second view of the projection is determined based characteristics of the first portion of the face. The second view is then rendered according to the scaling factor. The use of the scaling factor to render the second view causes a change in the depiction of the second portion of the face. For example, the scaling factor can indicate to change the resolution or expected size of the second portion of the face when rendering the second view. A face is then detected within the spherical image based on the rendered first and second views.

Abstract: Systems and methods are disclosed for non-local means denoising of images. For example, methods may include receiving an image from an image sensor; determining a set of non-local means weights for the image; applying the set of non-local means weights to the image to obtain a first denoised image; applying the set of non-local means weights to the first denoised image to obtain a second denoised image; and storing, displaying, or transmitting an output image based on the second denoised image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving an image from an image sensor; applying a filter to the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: An image capture device may include an image sensor, a processor, and memory. The image sensor may be configured to obtain an image. The processor may be configured to: generate a grid on the image forming tiles; determine a fringing level of each vertex of the vertices; sort all of the tiles based on the fringing level of each tile so that the tiles are sorted in a descending order from the tile with a highest of the fringing levels to the tile with a lowest of the fringing levels; and apply a fringing compensation to a subset of the sorted tiles to obtain a processed image. The memory may be configured to store the processed image.

Abstract: Flare compensation includes receiving a first image and a second image; converting the first and the second images from an RGB domain to a YUV domain; obtaining an intensity differences profile along a stitch line between the first and the second images, where the intensity differences profile is obtained for the Y component; obtaining a dark corner intensity differences profile between the first and the second images based on a relative illumination of an area outside a first image circle of the first image and a second image circle of the second image, where the dark corner intensity differences profile is obtained for the Y component; obtaining a flare profile using the intensity differences profile and the dark corner intensity differences profile; converting the flare profile of the Y component to an RGB flare profile; and modifying one of the first or second images based on the RGB flare profile.

Abstract: A system accesses an image with each pixel of the image having luminance values each representative of a color component of the pixel. The system generates a first histogram for aggregate luminance values of the image, and accesses a target histogram for the image representative of a desired global image contrast. The system computes a transfer function based on the first histogram and the target histogram such that when the transfer function is applied, a histogram of the modified aggregate luminance values is within a threshold similarity of the target histogram. The system modifies the image by applying the transfer function to the luminance values of the image to produce a tone mapped image, and outputs the modified image.

Abstract: An image capture device may include an image sensor, a processor, and a memory. The image sensor may be configured to obtain an image. The processor may be configured to generate a grid on the image. The grid may include one or more vertices. The one or more vertices may be used to form tiles. The processor may be configured to determine a flare level of each vertex. The processor may be configured to assign a maximum flare level for each tile of the image. The processor may be configured to sort the tiles. The tiles may be sorted based on the maximum flare level of each tile. The processor may be configured to apply a flare compensation to a subset of the tiles to obtain a processed image. The processed image may have reduced flare artifacts or no flare artifacts. The processed image may be stored in the memory.

Abstract: Systems and methods are disclosed for high dynamic rate processing based on angular rate measurements. For example, methods may include receiving a short exposure image that was captured using an image sensor; receiving a long exposure image that was captured using the image sensor; receiving an angular rate measurement captured using an angular rate sensor attached to the image sensor during exposure of the long exposure image; determining, based on the angular rate measurement, whether to apply high dynamic range processing to an image portion of the short exposure image and the long exposure image; and responsive to a determination not to apply high dynamic range processing to the image portion, selecting the image portion of the short exposure image for use as the image portion of an output image and discard the image portion of the long exposure image.

Abstract: Systems and methods are disclosed for image signal processing. For example, systems may include an image sensor and a processing apparatus. The image sensor captures image data using a plurality of selectable exposure times. The processing apparatus receives a first image from the image sensor captured with a first exposure time and receives a second image from the image sensor captured with a second exposure time that is less than the first exposure time. A high dynamic range image is determined based on the first image and the second image, wherein an image portion of the high dynamic range image is based on a corresponding image portion of the second image when a pixel of a corresponding image portion of the first image is saturated. An output image that is based on the high dynamic range image is stored, displayed, or transmitted.