H04N19/31

Image decoding method and apparatus using same

The present invention includes an image information decoding method which comprises: a step of receiving a bitstream that includes a network abstraction layer (NAL) unit including information related to an encoded image; and a step of parsing an NAL unit header of the NAL unit. The NAL unit header includes layer information including reserved_one_5bits for identifying an extended layer in an extended bitstream and temporal_id for identifying a temporal layer of a bitstream. The reserved_one_5bits of the layer information is received prior to the temporal_id of the layer information. Thus, a method for describing scalability information in a hierarchical bitstream is provided.

Image decoding method and apparatus using same

The present invention includes an image information decoding method which comprises: a step of receiving a bitstream that includes a network abstraction layer (NAL) unit including information related to an encoded image; and a step of parsing an NAL unit header of the NAL unit. The NAL unit header includes layer information including reserved_one_5bits for identifying an extended layer in an extended bitstream and temporal_id for identifying a temporal layer of a bitstream. The reserved_one_5bits of the layer information is received prior to the temporal_id of the layer information. Thus, a method for describing scalability information in a hierarchical bitstream is provided.

Video encoding method, video decoding method, video encoding apparatus, and video decoding apparatus

A video encoding method of performing scalable encoding on input video includes: determining a total number of layers of the scalable encoding to be less than or equal to a maximum layer count determined according to a frame rate; and performing the scalable encoding on the input video to generate a bitstream, using the determined total number of layers.

Video encoding method, video decoding method, video encoding apparatus, and video decoding apparatus

A video encoding method of performing scalable encoding on input video includes: determining a total number of layers of the scalable encoding to be less than or equal to a maximum layer count determined according to a frame rate; and performing the scalable encoding on the input video to generate a bitstream, using the determined total number of layers.

Sub-picture Position Constraints In Video Coding
20250234023 · 2025-07-17 ·

A video coding mechanism is disclosed. The mechanism includes receiving a bitstream comprising a plurality of sub-pictures partitioned from a picture such that a union of the sub-pictures covers a total area of the picture without overlap. The bitstream is parsed to obtain the one or more sub-pictures. The one or more sub-pictures are decoded to create a video sequence. The video sequence is forwarded for display.

Layered random access with reference picture resampling

A method of decoding an encoded video bitstream using at least one processor, including obtaining a coded base layer picture and a coded enhancement layer picture included in an LRA access unit; determining whether a random access occurs at the LRA access unit; based on the random access not occurring at the LRA access unit, generating a reconstructed base layer picture by reconstructing the coded base layer picture, and generating a reconstructed enhancement layer picture by reconstructing the coded enhancement layer picture using the reconstructed base layer picture and a previously reconstructed picture; based on the random access occurring at the LRA access unit, generating the reconstructed base layer picture by reconstructing the coded base layer picture, and generating the reconstructed enhancement layer picture by upsampling the reconstructed base layer picture; and outputting the reconstructed enhancement layer picture.

Picture coding and decoding

A picture with multiple slices is encoded by generating a coded slice representation for each of the slices. A slice flag is set to a first value for the first slice in the picture and corresponding slice flags of the remaining slices are set to a second defined value. A respective slice address is generated for each remaining slice to enable identification of the slice start position within the picture for the slice. A coded picture representation of the picture comprises the coded slice representations, the slice addresses and the slice flags. The slice flags enable differentiation between slices for which slice addresses are required and the slice per picture for which no slice address is needed to identify its slice start position.

Picture coding and decoding

A picture with multiple slices is encoded by generating a coded slice representation for each of the slices. A slice flag is set to a first value for the first slice in the picture and corresponding slice flags of the remaining slices are set to a second defined value. A respective slice address is generated for each remaining slice to enable identification of the slice start position within the picture for the slice. A coded picture representation of the picture comprises the coded slice representations, the slice addresses and the slice flags. The slice flags enable differentiation between slices for which slice addresses are required and the slice per picture for which no slice address is needed to identify its slice start position.

Machine learning for visual processing

A method for developing an enhancement model for low-quality visual data, the method comprising the steps of receiving one or more sections of higher-quality visual data; and training a hierarchical algorithm. The hierarchical algorithm is operable to increase the quality of one or more sections of lower-quality visual data so as to substantially reproduce the one or more sections of higher-quality visual data. The hierarchical algorithm is then outputted.

Machine learning for visual processing

A method for developing an enhancement model for low-quality visual data, the method comprising the steps of receiving one or more sections of higher-quality visual data; and training a hierarchical algorithm. The hierarchical algorithm is operable to increase the quality of one or more sections of lower-quality visual data so as to substantially reproduce the one or more sections of higher-quality visual data. The hierarchical algorithm is then outputted.