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: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a first image from a first image sensor; receiving a second image from a second image sensor; determining an electronic rolling shutter correction mapping for the first image and the second image; determining a parallax correction mapping based on the first image and the second image for stitching the first image and the second image; determining a warp mapping based on the parallax correction mapping and the electronic rolling shutter correction mapping, wherein the warp mapping applies the electronic rolling shutter correction mapping after the parallax correction mapping; applying the warp mapping to image data based on the first image and the second image to obtain a composite image; and storing, displaying, or transmitting an output image that is based on the composite image.

Abstract: Apparatus and methods for the stitch zone calculation of a generated projection of a spherical image. In one embodiment, a computing device is disclosed which includes logic configured to: obtain a plurality of images; map the plurality of images onto a spherical image; re-orient the spherical image in accordance with a desired stitch line and a desired projection for the desired stitch line; and map the spherical image to the desired projection having the desired stitch line. In a variant, the desired stitch line is mapped onto an optimal stitch zone, the optimal stitch zone characterized as a set of points that defines a single line on the desired projection in which the set of points along the desired projection lie closest to the spherical image in a mean square sense.

Abstract: Video content may be captured by an image capture device during a capture duration. The video content may include video frames that define visual content viewable as a function of progress through a progress length of the video content. Rotational position information may characterize rotational positions of the image capture device during the capture duration. Time-lapse video frames may be determined from the video frames of the video content based on a spatiotemporal metric. The spatiotemporal metric may characterize spatial smoothness and temporal regularity of the time-lapse video frames. The spatial smoothness may be determined based on the rotational positions of the image capture device corresponding to the time-lapse video frames, and the temporal regularity may be determined based on moments corresponding to the time-lapse video frames. Time-lapse video content may be generated based on the time-lapse video frames.

Abstract: An image or a video may include a spherical capture of a scene. A punchout of the image or the video may provide a panoramic view of the scene.

Abstract: Methods and apparatus for processing of high resolution content so as to obey desired encoder constraints. In one embodiment, the method includes capturing high resolution imaging spherical content; mapping the spherical content to another frame of reference (e.g., a non-uniform mapping and scaling) splitting up the mapped and scaled content into respective portions; feeding the split up portions to respective imaging encoders; packing encoded content from the respective imaging encoders into an A/V container; and storing and/or transmitting the A/V container. In one variant, the mapping and scaling are chosen to enable rendering of 1080P content in a desired scope or range (e.g., 360 degrees) using commodity encoder hardware and software.

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: Methods and apparatus for processing of video content to optimize codec bandwidth. In one embodiment, the method includes capturing panoramic imaging content (e.g., a 360° panorama), mapping the panoramic imaging content into an equi-angular cubemap (EAC) format, and splitting the EAC format into segments for transmission to maximize codec bandwidth. In one exemplary embodiment, the EAC segments are transmitted at a different frame rate than the subsequent display rate of the panoramic imaging content. For example, the mapping and frame rate may be chosen to enable the rendering of 8K, 360-degree content at 24 fps, using commodity encoder hardware and software that nominally supports 4K content at 60 fps.

Abstract: Methods and apparatus for processing of video content to optimize codec bandwidth. In one embodiment, the method includes capturing panoramic imaging content (e.g., a 360° panorama), mapping the panoramic imaging content into an equi-angular cubemap (EAC) format, and splitting the EAC format into segments for transmission to maximize codec bandwidth. In one exemplary embodiment, the EAC segments are transmitted at a different frame rate than the subsequent display rate of the panoramic imaging content. For example, the mapping and frame rate may be chosen to enable the rendering of 8K, 360-degree content at 24 fps, using commodity encoder hardware and software that nominally supports 4K content at 60 fps.

Abstract: Systems and methods are disclosed for image capture. For example, methods may include accessing a sequence of images from an image sensor; determining a sequence of parameters for respective images in the sequence of images based on the respective images; storing the sequence of images in a buffer; determining a temporally smoothed parameter for a current image in the sequence of images based on the sequence of parameters, wherein the sequence of parameters includes parameters for images in the sequence of images that were captured after the current image; applying image processing to the current image based on the temporally smoothed parameter to obtain a processed image; and storing, displaying, or transmitting an output image based on the processed image.

Abstract: Visual content is captured by an image capture device during a capture duration. The image capture devices experiences motion during the capture duration. The intentionality of the motion of the image capture device is determined based on angular acceleration of the image capture device during the capture duration. A punchout of the visual content is determined based on the intentionality of the motion of the image capture device. The punchout of the visual content is used to generate stabilized 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: Apparatus and methods for the stitch zone calculation of a generated projection of a spherical image. In one embodiment, a computing device is disclosed which includes logic configured to: obtain a plurality of images; map the plurality of images onto a spherical image; re-orient the spherical image in accordance with a desired stitch line and a desired projection for the desired stitch line; and map the spherical image to the desired projection having the desired stitch line. In a variant, the desired stitch line is mapped onto an optimal stitch zone, the optimal stitch zone characterized as a set of points that defines a single line on the desired projection in which the set of points along the desired projection lie closest to the spherical image in a mean square sense.

Abstract: Image signal processing may include desaturation control, which may include adaptive desaturation control. Image signal processing with desaturation control may include obtaining, by an image signal processor, from an image sensor, an input image signal representing an input image, obtaining, by the image signal processor, color correction information for the input image, obtaining a color corrected image based on the input image using color correction with desaturation control such that inaccurate colorization of the color corrected image is minimized, and outputting the color corrected 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: Visual content is captured by an image capture device during a capture duration. The image capture devices experiences motion during the capture duration. The intentionality of the motion of the image capture device is determined based on angular acceleration of the image capture device during the capture duration. A punchout of the visual content is determined based on the intentionality of the motion of the image capture device. The punchout of the visual content is used to generate stabilized visual content.

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: 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 signal processing may include obtaining a first portion of a first input image, the first portion having a defined width, a defined height, and a defined portion size, which is a product of multiplying the defined width by the defined height, the first portion of the first input image including a first set of image elements in raster order and having a cardinality of the defined portion size. Image signal processing may include sequential in-place blocking transposition of the first input image, which may include using a buffer, omit using another buffer, and has linear complexity, and may include buffering the first set of image elements using the buffer, the buffer having a defined buffer size within twice the defined portion size, and outputting the first set of image elements from the buffer in block order.

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.