Disclosed is a low-complexity and yet efficient lossy method to compress distortion information for motion estimation, resulting in significant reduction in needed storage capacity. A system for implementing the method and a computer-readable medium for storing the method are also disclosed. The method includes determining and storing a distortion value for each trial motion vector in a plurality of trial motion vectors. Each trial motion vector specifies a position of a search region relative to a reference frame. The method further includes compressing each of the distortion values as a fixed number of bits based upon a minimum distortion value amongst the stored distortion values, and re-storing each compressed distortion value in place of its uncompressed value.

A method and apparatus for transmitting a desktop display comprising classifying a first region of the desktop display as persistently changed and a second region of the desktop display as sporadically changed, adjusting, in relation to a user experience (UX) bias and a resource constraint, a target image quality for the first region, decimating the first region in accordance with a spatial decimation factor to generate a first decimated region, compressing the first decimated region at the target image quality and compressing the second region to generate a plurality of compressed regions and transmitting the plurality of compressed regions to a client via an IP network.

An example device for decoding video data includes a memory configured to store video data and one or more processors implemented in circuitry and configured to determine a maximum possible value for a secondary transform syntax element for a block of video data, entropy decode a value for the secondary transform syntax element of the block to form a binarized value representative of the secondary transform for the block, reverse binarize the value for the secondary transform syntax element using a common binarization scheme regardless of the maximum possible value to determine the secondary transform for the block, and inverse-transform transform coefficients of the block using the determined secondary transform.

A method for processing high dynamic range data from a nonlinear camera includes; generating an input image comprising a plurality of pixels, each pixel having an initial pixel value, wherein the initial pixel values are generated using a camera transition curve; generating a first lookup table representing a combination of an inverse function and a re-compression function, the first lookup table having input values and output values, wherein each input value is linked to one output value, the inverse function is the inverse of the camera transition curve, the re-compression function is a smooth and continuous function having a slope at each input value which is greater than or equal to a corresponding slope of the camera transition curve, the first lookup table is generated such that the inverse function precedes the re-compression function; and generating a first image by converting the initial pixel values using the first lookup table.

A method of dividing an input image signal into pixel blocks, and performing inter-prediction on the divided pixel blocks. This method includes selecting predicted motion information from a motion information buffer storing motion information in an encoded region, and predicting motion information of an encoding target block by using the predicted motion information. The method further includes acquiring representative motion information from a plurality of items of motion information in an encoded region in accordance with first information indicating a method of selecting the predicted motion information, thereby obtaining only the representative motion information.

In one example, the present disclosure describes a device, computer-readable medium, and method for enabling secure video sharing by exploiting data sparsity. In one example, the method includes applying a transformation to a video dataset containing a plurality of video samples, to produce a plurality of sparse vectors in a first dimensional space, wherein each sparse vector of the plurality of sparse vectors corresponds to one video sample of the plurality of video samples, and multiplying each sparse vector of the plurality of sparse vectors by a transformation matrix to produce a plurality of reduced vectors in a second dimensional space, wherein the dimension of the second dimensional space is smaller than a dimension of the first dimensional space, and wherein the plurality of reduced vectors in the second dimensional space hides information about the video dataset while preserving relational properties between the plurality of video samples.

The present disclosure provides systems and methods for performing adaptive resolution change during video encoding and decoding. The methods include: comparing resolutions of a target picture and a first reference picture; in response to the target picture and the first reference picture having different resolutions, resampling the first reference picture to generate a second reference picture; and encoding or decoding the target picture using the second reference picture.

A video decoding method according to the present invention may comprise: a step for determining whether to divide a current block into a plurality of sub-blocks; a step for determining an intra prediction mode for the current block; and a step for performing intra prediction for each sub-block on the basis of the intra prediction mode, when the current block is divided into the plurality of sub-blocks.

An image processing apparatus for performing correction for each frame group including a predetermined number of frames into which video data is divided includes a decoding unit configured to obtain a corrected frame group by correcting a second frame group, which is a frame group continuous with a first frame group in time, using a feature quantity of the first frame group. The decoding unit performs the correction so that subjective image quality based on a relationship between the second frame group and a frame group subsequent to the second frame group in time is increased and so that a predetermined classifier classifies that a frame group in which the second frame group is concatenated with the frame group subsequent to the second frame group in time is the same as a frame group in which the corrected frame group is concatenated with a corrected frame group obtained by correcting the frame group subsequent to the second frame group in time.

Devices, systems and methods for digital video coding, which includes reference picture resampling, are described. An example method for video processing includes performing a conversion between a video comprising one or more video segments comprising one or more video units and a bitstream representation of the video, wherein the bitstream representation conforms to a format rule and comprises information related to an adaptive resolution conversion (ARC) process, wherein the format rule specifies the applicability of the ARC process to a video segment, wherein an indication that the one or more video units of the video segment are coded with different resolutions is included in the bitstream representation in a syntax structure that is different from a header syntax structure, a decoder parameter set, a video parameter set, a picture parameter set, a sequence parameter set, and an adaptation parameter set.