Aspects of the disclosure provide a method and an apparatus for video decoding. Processing circuitry of the apparatus can decode prediction information of a current block to be reconstructed from a coded video bitstream. The prediction information can be indicative of an inter prediction mode. The processing circuitry can add motion information of a previously decoded block to a candidate list for the current block as a new motion information candidate based on a comparison between a first hash value of the motion information of the previously decoded block and one or more hash values of motion information candidates in the candidate list. The processing circuitry can reconstruct at least one sample of the current block based on current motion information of the current block that is determined based on the candidate list.

A method of compressing image data comprising a set of image values each representing a position in image-value space so as to define an occupied region thereof. The method comprises selectively applying a series of compression transforms to subsets of the image data items to generate a transformed set of image data items occupying a compacted region of value space. The method further comprises identifying a set of one or more reference data items that quantizes the compacted region in value space. For each image data item in the set of image data items, a sequence of decompression transforms from a fixed set of decompression transforms is identified that generates an approximation of that image data item when applied to a selected one of the one or more reference data items. Each image data item in the set of image data items is encoded as a representation of the identified sequence of decompression transforms for that image data item. The encoded image data items, set of reference data items and the fixed set of decompression transforms are stored as compressed image data.

A method of compressing image data comprising a set of image values each representing a position in image-value space so as to define an occupied region thereof. The method comprises selectively applying a series of compression transforms to subsets of the image data items to generate a transformed set of image data items occupying a compacted region of value space. The method further comprises identifying a set of one or more reference data items that quantizes the compacted region in value space. For each image data item in the set of image data items, a sequence of decompression transforms from a fixed set of decompression transforms is identified that generates an approximation of that image data item when applied to a selected one of the one or more reference data items. Each image data item in the set of image data items is encoded as a representation of the identified sequence of decompression transforms for that image data item. The encoded image data items, set of reference data items and the fixed set of decompression transforms are stored as compressed image data.

In an embodiment, a method involves accessing a first pixel block of an image, the first pixel block comprising pixels, each associated with multiple pixel components, determining whether to separately or jointly encode the multiple pixel components of each of the pixels of the first pixel block, determining that the multiple pixel components of each of the pixels in the first pixel block are to be jointly encoded based on (1) determining, based on the multiple pixel components of each of the pixels, a line defined within a three-dimensional coordinate system in which each of the pixels is represented as a three-dimensional point and (2) determining that the line satisfies a predetermined criteria, and encoding the multiple pixel components of each of the pixels in the first pixel block as a single quantized value based on a projection of the three-dimensional point associated with that pixel onto the line.

A method in a rate adaptive system includes categorizing, by an encoder, a plurality of clusters of data in a segmented image into one of a plurality of categories corresponding to a different predetermined label with a predetermined priority level; vectorizing, by the encoder, the data to generate a sparse vector x.sub.i for its corresponding label; encoding, by the encoder, a plurality of the sparse vectors x.sub.i by multiplying a measurement matrix A.sub.i(t) with the sparse vector x.sub.i to generate a set of encoded information y.sub.i; transmitting, by the encoder to the decoder, the plurality of sets of the encoded information y.sub.i in a prioritized order; decoding, by the decoder, the plurality of sets of encoded information y.sub.i to determine the plurality of the sparse vectors x.sub.i based on determining measurement matrix A.sub.i(t); and uniting the plurality of the sparse vectors x.sub.i into a single image frame.

A method of encoding a three-dimensional (3D) image including a point cloud includes grouping a plurality of points included in the point cloud into at least one segment; generating patches by projecting the points included in the segment onto a predetermined plane in a first direction or a second direction; generating two-dimensional (2D) images by packing the patches; and generating and outputting a bitstream including information about a direction in which each point is projected to generate the patches and information about the 2D images.

A method of encoding a three-dimensional (3D) image including a point cloud includes grouping a plurality of points included in the point cloud into at least one segment; generating patches by projecting the points included in the segment onto a predetermined plane in a first direction or a second direction; generating two-dimensional (2D) images by packing the patches; and generating and outputting a bitstream including information about a direction in which each point is projected to generate the patches and information about the 2D images.

Computer processor hardware receives a first set of adjustment values. The first set of adjustment values specify adjustments to be made to a predicted rendition of a signal generated at a first level of quality to reconstruct a rendition of the signal at the first level of quality. The computer processor hardware processes the first set of adjustment values and derives a second set of adjustment values based on the first set of adjustment values and a rendition of the signal at a second level of quality. The second level of quality is lower than the first level of quality.

Computer processor hardware receives a first set of adjustment values. The first set of adjustment values specify adjustments to be made to a predicted rendition of a signal generated at a first level of quality to reconstruct a rendition of the signal at the first level of quality. The computer processor hardware processes the first set of adjustment values and derives a second set of adjustment values based on the first set of adjustment values and a rendition of the signal at a second level of quality. The second level of quality is lower than the first level of quality.

Techniques are provided herein for more efficiently storing images that have a common subject, such as product images that share the same product in the image. Each image undergoes an adaptive tiling procedure to split the image into a plurality of tiles, with each tile identifying a region of the image having pixels with the same content. The tiles across multiple images can then be clustered together and those tiles having identical content are removed. Once all duplicate tiles have been removed from the set of all tiles across the images, the tiles are once again clustered based on their encoding scheme and certain encoding parameters. Tiles within each cluster are compressed using the best compression technique for the tiles in each corresponding cluster. By removing duplicative tile content between numerous images of the same subject, the total amount of data that needs to be stored is reduced.