Entropy coding for video encoding and decoding

By reducing the number of contexts in CABAC through context sharing and eliminating adjacent block dependencies, the solution addresses the challenge of high complexity and low efficiency in video encoding and decoding, resulting in improved compression and decoding performance.

JP7864872B2Active Publication Date: 2026-05-25INTERDIGITAL VC HOLDINGS INC
View PDF 0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
INTERDIGITAL VC HOLDINGS INC
Filing Date
2025-01-06
Publication Date
2026-05-25

AI Technical Summary

Technical Problem

Existing video encoding and decoding technologies face challenges in achieving high compression efficiency and reduced complexity, particularly in the context-based adaptive binary arithmetic coding (CABAC) process, due to the large number of contexts required for entropy coding, which affects decoding efficiency and complexity.

Method used

The proposed solution involves reducing the number of contexts used in CABAC by deriving context models based on adjacent syntax elements, sharing contexts for different bin indices of the same block size, and eliminating the need for context derivation from adjacent blocks, thereby simplifying the encoding and decoding processes.

Benefits of technology

This approach reduces the complexity of entropy coding, enhances compression efficiency, and decreases the computational load on decoders, leading to improved video encoding and decoding performance.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure 0007864872000009
    Figure 0007864872000009
  • Figure 0007864872000010
    Figure 0007864872000010
  • Figure 0007864872000011
    Figure 0007864872000011
Patent Text Reader

Abstract

To provide various approaches or modifications for entropy coding.SOLUTION: A method for encoding or decoding at least one bin of a binarization of a syntax element for a block of a luma component of a video includes the steps of obtaining a set of context models associated with bin indexes of the binarization of the syntax element, where two or more bin indexes share a same context model of the set, deriving a context shift variable based on a size of the block, deriving a context model from the set of at least one bin based on the at least one bin index of the binarization and the context shift variable to provide a derived context model, and entropy encoding or entropy decoding the at least one bin using the derived context model.SELECTED DRAWING: Figure 16
Need to check novelty before this filing date? Find Prior Art