Abstract: Systems and methods are disclosed for sensor prioritization for composite image capture. For example, methods may include selecting an image sensor as a prioritized sensor from among an array of two or more image sensors; determining one or more image processing parameters based on one or more images captured using the prioritized sensor; applying image processing using the one or more image processing parameters to images captured with each image sensor in the array of two or more image sensors to obtain respective processed images for the array of two or more image sensors; and stitching the respective processed images for the array of two or more image sensors to obtain a composite image.

Abstract: Flare compensation includes obtaining a dark corner intensity differences profile between a first and a second image 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. The dark corner intensity differences profile is obtained for a luminance (Y) component. A flare profile is obtained using an intensity differences profile and the dark corner intensity differences profile. The intensity differences profile is obtained for the Y component along a stitch line between the first image and the second image. The flare profile of the Y component is converted to an RGB flare profile. The first image is modified based on the RGB flare profile to obtain a processed first image.

Abstract: Image analysis and processing may include a multiple-tone-control (MTC) unit configured to obtain a tone-control gain lookup table, a plurality of MTC gain lookup tables, wherein the input image is divided into a plurality of blocks and wherein the plurality of MTC gain lookup tables includes a respective MTC gain lookup table corresponding to each respective block from the plurality of blocks, MTC grid parameters, MTC weighting parameters, a tone-control gain based on the tone-control gain lookup table, a MTC gain based on at least one MTC gain lookup table from the plurality of MTC gain lookup tables, the MTC grid parameters, and the MTC weighting parameters, and an output value based on the tone-control gain and the MTC gain.

Abstract: An image capture device may capture two hemispherical views of a scene. The two hemispherical view of the scene may be stitched along a stitch line. The image capture device may be rotated to align the stitch line with a mid-line of a panoramic field of view of the scene. Separate exposure settings may be used to capture the two hemispherical views of the scene, with the exposure settings increasing the dynamic range of the scene depicted within the panoramic field of view of the scene. The panoramic field of view of the scene may be punched out as panoramic visual content.

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: Systems and methods are disclosed for image signal processing. For example, methods may include accessing an image from an image sensor; detecting an object area on the image; classifying the object area on the image; applying a filter to an object area of 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: 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: 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: Optical element(s) of an image capture device may be changed. Characteristic(s) of the optical element(s) may be determined based on shading map corresponding to an image captured by the image capture device and the lighting condition during the capture of the image. The image capture device may be operated in accordance with the determined characteristic(s) of the optical element(s).

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: Image capture devices and methods may use field variable tone mapping for 360 content. An image capture device may comprise an image sensor and a processor. The image sensor may capture a hyper-hemispherical image that includes an image circle portion. The processor may perform local tone mapping (LTM) on a first area of the image circle portion and perform global tone mapping (GTM) on a second area of pixels of the image circle portion. The GTM may be performed on a condition that a portion of a predefined area of pixels overlaps with a stitch line. The processor may be configured to stitch the hyper-hemispherical image and a second hyper-hemispherical image at the stitch line to obtain a processed image. The processor may be configured to display, store, output, or transmit the processed image.

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: Methods for parameter alignment processing are described herein. An image capture device includes a first image capture device configured to capture a first image, a second image capture device configured to capture a second image, and an image signal processor connected to the first image capture device and to the second image capture device. The image signal processor is configured to apply, to the first image and the second image, at least two of a respective luminance lens shading (LLS) compensation factor, a respective color lens shading (CLS) compensation factor, a respective exposure difference compensation factor, a respective white balance compensation factor, a respective lens exposure correction (LEC) compensation factor, and a respective flare compensation factor, blend the compensated first image and the compensated second image to form a blended image, and output an image based on the blended image.

Abstract: Auto exposure processing for spherical images improves image quality by reducing visible exposure level variation along a stitch line within a spherical image. An average global luminance value is determined based on auto exposure configurations of first and second image sensors. Delta luminance values are determined for each of the image sensors based on the average global luminance value and a luminance variance between the image sensors. The auto exposure configurations of the image sensors are then updated using the delta luminance values, and the updated auto exposure configurations are used to capture images which are then combined to produce the spherical image. In some cases wherein updating the auto exposure configurations using the delta luminance values would breach a threshold representing a target luminosity for the scene, the use of the delta luminance values may be limited or those values may instead be discarded.

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 multiple-tone-control (MTC) unit configured to obtain a tone-control gain lookup table, a plurality of MTC gain lookup tables, wherein the input image is divided into a plurality of blocks and wherein the plurality of MTC gain lookup tables includes a respective MTC gain lookup table corresponding to each respective block from the plurality of blocks, MTC grid parameters, MTC weighting parameters, a tone-control gain based on the tone-control gain lookup table, a MTC gain based on at least one MTC gain lookup table from the plurality of MTC gain lookup tables, the MTC grid parameters, and the MTC weighting parameters, and an output value based on the tone-control gain and the MTC gain.

Abstract: 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. The gain value may be progressively increased from an approximate center of the first image to an edge of the first image to a common exposure level. The gain value may be progressively decreased from an approximate center of the second image to an edge of the second image to the common exposure level. Gain values may be scaled on each color channel for a pixel based on a saturation level of the pixel.

Abstract: Image capture devices and methods may use field variable tone mapping for 360 content. An image capture device may comprise an image sensor and a processor. The image sensor may capture a hyper-hemispherical image that includes an image circle portion and a dark corner portion. The processor may perform local tone mapping (LTM) on a first area of the image circle portion and perform global tone mapping (GTM) on a second area of pixels of the image circle portion. The GTM may be performed on a condition that a portion of a predefined area of pixels overlaps with a stitch line. The processor may be configured to stitch the hyper-hemispherical image and a second hyper-hemispherical image at the stitch line to obtain a processed image. The processor may be configured to display, store, output, or transmit the processed image.