Video coding method and decoding method, bit stream storage method and device, electronic equipment and storage medium

By integrating semantic segmentation and saliency detection models and adjusting quantization parameters, differentiated video coding is achieved, solving the problem of false positives in saliency detection and improving coding quality and user experience.

CN121940545APending Publication Date: 2026-04-28BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
0 Cites 3 Cited by

Patent Information

Application Number
CN202610129564.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-29
Publication Date
2026-04-28

AI Technical Summary

Technical Problem

Existing video coding methods fail to effectively distinguish the semantic meaning of image regions, which may lead to misjudgments by saliency detection algorithms. Unimportant regions are incorrectly assigned high bitrates while important regions are ignored, affecting coding quality.

Method used

By combining semantic segmentation and saliency detection models, the quantization parameter values ​​of pixel blocks are adjusted by calculating the quantization parameter increment, thereby achieving differentiated encoding. This approach optimizes the allocation of encoding resources by considering semantic type, saliency, and texture complexity.

Benefits of technology

This effectively reduces misjudgments, ensures that encoded resources are allocated to areas that better align with human subjective perception, improves the user viewing experience, and saves bitrate resources.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to a video coding method, a video decoding method, a bit stream storage method, a bit stream storage device, electronic equipment and a storage medium, and the method comprises the following steps: for each pixel block in a plurality of pixel blocks contained in a current video frame, executing the following operations: identifying a target semantic type of the content contained in the pixel block by using a semantic segmentation model, detecting the target saliency degree of the content contained in the pixel block by using a saliency detection model; calculating a quantization parameter increment based on the target semantic type and the target saliency degree; adjusting the quantization parameter value of the pixel block based on the quantization parameter increment; and encoding the pixel block based on the adjusted quantization parameter value.
Need to check novelty before this filing date? Find Prior Art