Abstract: A non-transitory computer-readable storage medium stores executable instructions that, when executed by a processor, cause performance of operations comprising operations to access an image captured by an image sensor, obtain a transfer function for mapping pixel values, determine a faces indication that reflects a proportion of a scene depicted in the image that includes one or more human faces, and modify the transfer function based on the faces indication. Modifying the transfer function based on the faces indication comprises adjusting a gain of the transfer function to move the gain closer to unity. The operations include to apply the transfer function to pixel values of the image to produce a tone mapped image and output the tone mapped image.

Abstract: An image is processed using a combination of techniques, particularly, in which low frequency information is processed using multiple tone control and high frequency information is processed using local tone mapping. An image is divided into a plurality of blocks including a given block. Low frequency information and high frequency information of the given block are separated. The low frequency information is processed using multiple tone control. The high frequency information is processed using local tone mapping. A processed image is then produced based on the processed low frequency information and based on the processed high frequency information, the processed image corresponding to the image captured using the image sensor. The processed image is then output for storage or display. Processing the low frequency information can include using a gain curve and bilinear interpolation. Processing the high frequency information can include using an edge preservation filter.

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 luminance values determined for first and second images, which are based on auto exposure configurations of first and second image sensors used to obtain those first and second images. Delta luminance values are determined for the first and second images using the average global luminance value. The first and second images are then updated using the delta luminance values, and the updated first and second images are used to produce a spherical 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 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: 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: 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: Field variable tone mapping is performed for 360 content. An image capture device includes an image sensor and a processor. The image sensor obtains a hyper-hemispherical image and the processor performs local tone mapping (LTM) on a first area of the hyper-hemispherical image and performs global tone mapping (GTM) on a second area of the hyper-hemispherical image to obtain a processed image. The processor may be configured to display, store, output, or transmit the processed 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: 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: Image signal processing includes obtaining two or more image signals from a first 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 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 processing a transformed base layer of the exposure compensated image to obtain a high dynamic range (HDR) image.

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: An image capture device may process first frames from a first image sensor obtained at a first frame rate and store the processed first frames in a memory. The image capture device may obtain first camera control statistics based at least on partially processed second frames from a second image sensor obtained at a second frame rate. The image capture device may switch a capture mode to obtain third frames at the second frame rate from the first image sensor and to obtain fourth frames at the first frame rate from the second image sensor.

Abstract: Auto exposure metering is adapted for spherical panoramic content. Using input image data, a first metering map is generated for a selected image sensor and a second metering map is generated for an unselected image sensor. Auto exposure level values for the selected image sensor and for the unselected image sensor are respectively metered using the first metering map and the second metering map, such as by adjusting luminance weights in certain locations of the respective image sensor panoramic image capture band. Hemispherical images are processed using the auto exposure metered level values and stitched together in a panoramic format to produce a spherical panoramic image. The metering maps are generated to account for areas of greatest image data importance relative to a primary orientation direction of the spherical panoramic image. This allows for effective auto exposure metering of such areas within the resulting spherical panoramic 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: Systems and methods are disclosed for non-linear color correction. The method including receiving an input image from an image sensor, converting the input image from a red, green, blue (RGB) color space format to an alternate color space format, determining localized hue correction parameters for a selected color in the alternate color space, determining localized saturation correction parameters for a selected hue in the alternate color space, applying the localized hue correction parameters and the localized saturation correction parameters to the input image to generate an output image and storing, displaying, or transmitting the output image based on at least the localized hue correction parameters and the localized saturation correction parameters.

Abstract: An image capture device may process first frames from a first image sensor obtained at a first frame rate and store the processed first frames in a memory. The image capture device may obtain first camera control statistics based at least on partially processed second frames from a second image sensor obtained at a second frame rate. The image capture device may switch a capture mode to obtain third frames at the second frame rate from the first image sensor and to obtain fourth frames at the first frame rate from the second image sensor.

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 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: 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.