Abstract: Image signal processing including generating image signal processing based encoding hints for motion estimation may include an image signal processor obtaining an input image portion of an input image from the input image signal, generating motion information for the input image portion, processing the input image portion based on the motion information, outputting processed image data, and outputting the motion information as encoding hints, such that the motion information is accessible by an encoder for generating an encoded output bitstream by obtaining the processed image data as source image data, obtaining the motion information, generating prediction data for encoding the source image data based on the motion information, generating encoded image data based on the prediction data, and including the encoded image data in an encoded output bitstream.

Abstract: Systems and methods for utilizing on-camera sensor information to improve video and/or image encoding quality are discussed herein. Specifically, the systems and methods described herein may utilize on-camera sensor information to adaptively adjust an intra frame insertion rate associated with a sequence of frames. The intra frame insertion rate associated with a sequence of frames may be adjusted based on the motion of the image capturing device while capturing the sequence of frames and a predefined motion threshold associated with the intra frame insertion rate of the sequence of frames. In some implementations, the intra frame insertion rate may be adjusted based on the activity being performed during the capture of the sequence of frames. As such, the encoding of one or more frames within a sequence of frames may be adaptively adjusted to better suit the scene depicted by the sequence of frames.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving, by an image signal processor, one or more input image signals from one or more image sensors; determining a mapping based on the input image signal(s), wherein the mapping includes records that associate image portions of an output image with corresponding image portions of the input image signal(s); sorting the records of the mapping according to an order of the corresponding image portions of the input image signal(s); applying, by the image signal processor, image processing to image portions of the input image signal(s) to determine image portions of one or more processed images in the order; and determining, by the image signal processor, the image portions of the output image based at least in part on the mapping and the corresponding image portions of the processed image(s) in the order.

Abstract: A camera system processes images based on image luminance data. The camera system includes an image sensor, an image pipeline, an encoder and a memory. The image sensor converts light incident upon the image sensor into raw image data. The image pipeline converts raw image data into color-space image data and calculates luminance levels of the color-space image data. The encoder can determine one or more of quantization levels, determining GOP structure or reference frame spacing for the color-space image data based on the luminance levels. The memory stores the color-space image data and the luminance levels.

Abstract: A camera system processes images based on image activity data. The camera system includes an image sensor, an image pipeline, an encoder and a memory. The image sensor converts light incident upon the image sensor into raw image data. The image pipeline converts raw image data into color-space image data and calculates activity variances of the color-space image data. The encoder can determine one or more of quantization levels, block type (Intra vs Inter), determining transform size and type, and determining GOP structure or reference frame spacing for the color-space image data based on the activity variances. The memory stores the color-space image data and the activity variances.

Abstract: A camera system processes images based on image luminance data. The camera system includes an image sensor, an image pipeline, an encoder and a memory. The image sensor converts light incident upon the image sensor into raw image data. The image pipeline converts raw image data into color-space image data and calculates luminance levels of the color-space image data. The encoder can determine one or more of quantization levels, determining GOP structure or reference frame spacing for the color-space image data based on the luminance levels. The memory stores the color-space image data and the luminance levels.

Abstract: Example methods and apparatuses including a picture parallel decoder are described herein. The picture parallel decoder includes an entropy pre-processing unit, an entropy transcoding unit, and a plurality of decoders. The entropy pre-processing unit may be configured to determine dependencies between frames of an encoded bitstream and to determine slice location data within the encoded bitstream based on dependencies between the frames. The entropy transcoding unit may be configured to transcode slices of the encoded bitstream based on the dependencies between frames. The plurality of decoders may be configured to decode two or more of the transcoded slices in parallel.

Abstract: Methods and apparatus for the encoding of imaging data using pre-stored imaging statistics. Many extant image capture devices, including without limitation, smartphones, handheld video cameras, and other types of image capture devices, typically include, for example, auto-exposure (AE), auto-white balance (AWB) and auto-focus (AF) modules in an image signal processing (ISP) pipeline. These modules within the ISP pipeline generate various imaging statistics which can be repurposed for the encoding process of video data. These imaging statistics can be utilized for a number of encoding processes including, without limitation, adjusting an encoder parameter value for the encoding process, adjustment of the motion estimation search range, insertion of intra-frames within the video data and the determination of whether to use explicit or implicit weighting prediction.

Abstract: Methods and apparatus for the stitching of images from a multi-camera array. In one embodiment, stitching is performed for a first image and a second image with an overlapping field of view by: encoding the first image to produce a first encoded image; encoding the second image to produce a second uncompressed encoded image; stitching the first image with the second image by: decoding the first encoded image to produce a decoded first image; storing the decoded first image in memory; accessing, by a stitching engine, the decoded first image from memory; accessing, by the stitching engine, the second uncompressed encoded image; stitching, by the stitching engine, the decoded first image with the accessed second uncompressed encoded image to produce a stitched image; and outputting, by the stitching engine, the stitched image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving, by an image signal processor, one or more input image signals from one or more image sensors; determining a mapping based on the input image signal(s), wherein the mapping includes records that associate image portions of an output image with corresponding image portions of the input image signal(s); sorting the records of the mapping according to an order of the corresponding image portions of the input image signal(s); applying, by the image signal processor, image processing to image portions of the input image signal(s) to determine image portions of one or more processed images in the order; and determining, by the image signal processor, the image portions of the output image based at least in part on the mapping and the corresponding image portions of the processed image(s) in the order.

Abstract: A camera system processes images based on image activity data. The camera system includes an image sensor, an image pipeline, an encoder and a memory. The image sensor converts light incident upon the image sensor into raw image data. The image pipeline converts raw image data into color-space image data and calculates activity variances of the color-space image data. The encoder can determine one or more of quantization levels, block type (Intra vs Inter), determining transform size and type, and determining GOP structure or reference frame spacing for the color-space image data based on the activity variances. The memory stores the color-space image data and the activity variances.

Abstract: A camera system processes images based on image luminance data. The camera system includes an image sensor, an image pipeline, an encoder and a memory. The image sensor converts light incident upon the image sensor into raw image data. The image pipeline converts raw image data into color-space image data and calculates luminance levels of the color-space image data. The encoder can determine one or more of quantization levels, determining GOP structure or reference frame spacing for the color-space image data based on the luminance levels. The memory stores the color-space image data and the luminance levels.

Abstract: Example methods and apparatuses including a picture parallel decoder are described herein. The picture parallel decoder includes an entropy pre-processing unit, an entropy transcoding unit, and a plurality of decoders. The entropy pre-processing unit may be configured to determine dependencies between frames of an encoded bitstream and to determine slice location data within the encoded bitstream based on dependencies between the frames. The entropy transcoding unit may be configured to transcode slices of the encoded bitstream based on the dependencies between frames. The plurality of decoders may be configured to decode two or more of the transcoded slices in parallel.

Abstract: A method for memory management in video decoding systems that avoids some of the costs and disadvantages with video decoding systems in the prior art. Some embodiments of the present invention are especially well-suited for use with the H.264 video decoding standard. The illustrative embodiment is a memory management technique that controls which data is in the fastest memory available to a processor performing video decoding. In particular, the technique seeks to ensure that the data the processor will need is in the primary memory and expunges data that the processor will not need. The technique is based upon an analysis of predictive video decoding standards, such as H.264. By employing this technique, the illustrative embodiment ensures the expedient decoding of video frames.

Abstract: A method of interfacing with a media accelerator which includes providing a commands layer, providing a capabilities layer, and providing a discontinuity layer. The commands layer sends commands to the media accelerator. The capabilities layer obtains application capabilities from an application. The discontinuity layer provides discontinuity commands to the media accelerator.

Abstract: A method for memory management in video decoding systems that avoids some of the costs and disadvantages with video decoding systems in the prior art. Some embodiments of the present invention are especially well-suited for use with the H.264 video decoding standard. The illustrative embodiment is a memory management technique that controls which data is in the fastest memory available to a processor performing video decoding. In particular, the technique seeks to ensure that the data the processor will need is in the primary memory and expunges data that the processor will not need. The technique is based upon an analysis of predictive video decoding standards, such as H.264. By employing this technique, the illustrative embodiment ensures the expedient decoding of video frames.

Abstract: A method and an apparatus are disclosed that seek to mitigate resource utilization during the video deblocking process of a video frame. The disclosed techniques are based on the observation that as long as the standardized filter order is preserved for those individual pixels that are filtered twice, such as corner pixels, it is unnecessary to filter across the entire video frame, first across one dimension, then across another. The video deblocker of the illustrative embodiment of the present invention deblocks the video frame by considering the pixels to be filtered on a macroblock-by-macroblock basis. In some embodiments, the deblocker deblocks the macroblock by considering the pixels to be filtered on a sub-block-by-sub-block basis. The disclosed techniques are advantageous over some techniques in the prior art because the deblocker is only required to read in all of the macroblocks in a video frame once.