H04N19/65

Machine-learned in-loop predictor for video compression

A compression system trains a compression model for an encoder and decoder. In one embodiment, the compression model includes a machine-learned in-loop flow predictor that generates a flow prediction from previously reconstructed frames. The machine-learned flow predictor is coupled to receive a set of previously reconstructed frames and output a flow prediction for a target frame that is an estimation of the flow for the target frame. In particular, since the flow prediction can be generated by the decoder using the set of previously reconstructed frames, the encoder may transmit a flow delta that indicates a difference between the flow prediction and the actual flow for the target frame, instead of transmitting the flow itself. In this manner, the encoder can transmit a significantly smaller number of bits to the receiver, improving computational efficiency.

Machine-learned in-loop predictor for video compression

A compression system trains a compression model for an encoder and decoder. In one embodiment, the compression model includes a machine-learned in-loop flow predictor that generates a flow prediction from previously reconstructed frames. The machine-learned flow predictor is coupled to receive a set of previously reconstructed frames and output a flow prediction for a target frame that is an estimation of the flow for the target frame. In particular, since the flow prediction can be generated by the decoder using the set of previously reconstructed frames, the encoder may transmit a flow delta that indicates a difference between the flow prediction and the actual flow for the target frame, instead of transmitting the flow itself. In this manner, the encoder can transmit a significantly smaller number of bits to the receiver, improving computational efficiency.

Cluster-based dependency signaling

The signalization of the inter-layer dependencies between layers of a multi-layered data stream is described. A good compromise between a too intensive restriction of the potential diversity of inter-layer dependencies on the one hand and a too complex signaling of the inter-layer dependencies on the other hand has been found by describing the inter-layer dependencies by way of a first inter-dependency syntax structure indicating inter-dependencies between pairs of different values representable by a base layer-ID and a second inter-dependency syntax structure indicating inter-dependencies between pairs of different values representable by an extension layer-ID, the base layer ID and extension layer ID indexing the layers the portions of the multi-layer data stream are associated with. In accordance with this concept, emphasis may be shifted between increased diversity of the signalizable inter-layer dependencies on the one hand and reduced side-information overhead for signaling the inter-layer dependencies on the other hand.

Cluster-based dependency signaling

The signalization of the inter-layer dependencies between layers of a multi-layered data stream is described. A good compromise between a too intensive restriction of the potential diversity of inter-layer dependencies on the one hand and a too complex signaling of the inter-layer dependencies on the other hand has been found by describing the inter-layer dependencies by way of a first inter-dependency syntax structure indicating inter-dependencies between pairs of different values representable by a base layer-ID and a second inter-dependency syntax structure indicating inter-dependencies between pairs of different values representable by an extension layer-ID, the base layer ID and extension layer ID indexing the layers the portions of the multi-layer data stream are associated with. In accordance with this concept, emphasis may be shifted between increased diversity of the signalizable inter-layer dependencies on the one hand and reduced side-information overhead for signaling the inter-layer dependencies on the other hand.

VIDEO ENCODING METHOD AND VIDEO DECODING METHOD

A video encoding method using a plurality of reference pictures includes: selecting whether or not a resilient picture referencing scheme is to be used for encoding video; writing a parameter indicating the selection into a header of an encoded video bitstream; and encoding a picture using inter-picture prediction using a result of the selection.

VIDEO ENCODING METHOD AND VIDEO DECODING METHOD

A video encoding method using a plurality of reference pictures includes: selecting whether or not a resilient picture referencing scheme is to be used for encoding video; writing a parameter indicating the selection into a header of an encoded video bitstream; and encoding a picture using inter-picture prediction using a result of the selection.

Methods for compressing and decompressing texture tiles and apparatuses using the same

The invention introduces a method for compressing texture tiles, which contains at least the following steps: lossless-compressing raw data of a texture tile; determining whether a length of the lossless-compression result of the raw data is greater than a target result; and when the length of the lossless-compression result of the raw data is greater than the target length, performing data-reduction control in layers for generating reduced data by reducing the raw data, and generating a lossless-compression result of the reduced data, thereby enabling the length of the lossless-compression result of the reduced data to be equal to the target length or shorter.

Methods for compressing and decompressing texture tiles and apparatuses using the same

The invention introduces a method for compressing texture tiles, which contains at least the following steps: lossless-compressing raw data of a texture tile; determining whether a length of the lossless-compression result of the raw data is greater than a target result; and when the length of the lossless-compression result of the raw data is greater than the target length, performing data-reduction control in layers for generating reduced data by reducing the raw data, and generating a lossless-compression result of the reduced data, thereby enabling the length of the lossless-compression result of the reduced data to be equal to the target length or shorter.

Image compression and decompression using controlled quality loss

The loss of image quality during compression is controlled using a sequence of quality control metrics. The sequence of quality control metrics is selected for quantizing transform coefficients within an area of the image based on an error level definition. Candidate bit costs are then determined by quantizing the transform coefficients according to the error level definition or a modified error level and the sequence of quality control metrics. Where the candidate bit cost resulting from using the modified error level is lower than the candidate bit cost resulting from using the error level definition, the transform coefficients are quantized according to the modified error level and the sequence of quality control metrics. Otherwise, the transform coefficients are quantized based on the error level definition and according to the sequence of quality control metrics.

Image compression and decompression using controlled quality loss

The loss of image quality during compression is controlled using a sequence of quality control metrics. The sequence of quality control metrics is selected for quantizing transform coefficients within an area of the image based on an error level definition. Candidate bit costs are then determined by quantizing the transform coefficients according to the error level definition or a modified error level and the sequence of quality control metrics. Where the candidate bit cost resulting from using the modified error level is lower than the candidate bit cost resulting from using the error level definition, the transform coefficients are quantized according to the modified error level and the sequence of quality control metrics. Otherwise, the transform coefficients are quantized based on the error level definition and according to the sequence of quality control metrics.