A video encoder may transform residual data by using a transform selected from a group of transforms. The transform is applied to the residual data to create a two-dimensional array of transform coefficients. A scanning mode is selected to scan the transform coefficients in the two-dimensional array into a one-dimensional array of transform coefficients. The combination of transform and scanning mode may be selected from a subset of combinations that is based on an intra-prediction mode. The scanning mode may also be selected based on the transform used to create the two-dimensional array. The transforms and/or scanning modes used may be signaled to a video decoder.

An encoding method is presented. Transform coefficients of a block are first obtained. They are then scanned according to a scan pattern for entropy coding. The scan pattern is determined responsive to a shape of the block.

FIG. 5

An encoding method is presented. Transform coefficients of a block are first obtained. They are then scanned according to a scan pattern for entropy coding. The scan pattern is determined responsive to a shape of the block.

FIG. 5

Disclosed is a data transmission system that transmits data by using a relay. The relay selects a transmission terminal from among a plurality of terminals accessing a base station. A base station transmits base station data to the relay during a first time slot, and the transmission terminal transmits terminal data to the relay. The relay transmits terminal data to the base station during a second time slot, and transmits base station data to the transmission terminal.

Disclosed is a data transmission system that transmits data by using a relay. The relay selects a transmission terminal from among a plurality of terminals accessing a base station. A base station transmits base station data to the relay during a first time slot, and the transmission terminal transmits terminal data to the relay. The relay transmits terminal data to the base station during a second time slot, and transmits base station data to the transmission terminal.

An image compression method includes parsing, by a processor, an image file to be compressed; and compressing, by the processor, the image file by ignoring a portion of bits of each pixel from among a plurality of pixels of the image file.

Method, apparatus, and non-transitory storage medium for end-to-end neural image compression using dependent scalar quantization with substitution, including receiving an input image; determining a substitute image based on the input image using a neural network based substitute feature generator; compressing the substitute image; quantizing the compressed substitute image to obtain a quantized representation of the input image with higher compression performance by using a first dependent scalar quantizer; and entropy encoding the substitute image using a neural network based encoder to generate a compressed representation of the quantized representation.

Method, apparatus, and non-transitory storage medium for end-to-end neural image compression using dependent scalar quantization with substitution, including receiving an input image; determining a substitute image based on the input image using a neural network based substitute feature generator; compressing the substitute image; quantizing the compressed substitute image to obtain a quantized representation of the input image with higher compression performance by using a first dependent scalar quantizer; and entropy encoding the substitute image using a neural network based encoder to generate a compressed representation of the quantized representation.

Aspects of the disclosure provide a method, an apparatus, and non-transitory computer-readable storage medium for video decoding. The apparatus includes processing circuitry that reconstructs blocks of an image that is to be reconstructed from a coded video bitstream. The processing circuitry decodes first deblocking information in the coded video bitstream including a first deblocking parameter of a deep neural network (DNN) in a video decoder. The first deblocking parameter of the DNN is an updated parameter that has been previously determined by a content adaptive training process. The processing circuitry determines the DNN for a first boundary region comprising a subset of samples in the reconstructed blocks based on the first deblocking parameter included in the first deblocking information. The processing circuitry deblocks the first boundary region comprising the subset of samples in the reconstructed blocks based on the determined DNN corresponding to the first deblocking parameter.

An image processing apparatus and an image processing method make it possible to suppress increase of the load of template matching. For each of motion vector candidates of accuracy rougher than accuracy of a motion vector candidate list, template matching between a template of a current block and a template of a reference block is performed to derive a cost, and elements of the motion vector candidate list are sorted on the basis of the derived costs of the motion vector candidates. Alternatively, for each of motion vector candidates of accuracy rougher than accuracy of a motion vector candidate list, template matching between a template of a current block and a template of a search point is performed to derive a cost, and a modification motion vector candidate is derived on the basis of the derived costs of the motion vector candidates.