Encoding method, apparatus, encoder, medium and product

By obtaining the encoding parameters of the unit to be encoded with high texture complexity through a subjective quality prediction model, the problem of low accuracy of encoding parameter decision-making in the existing technology is solved, and a more efficient encoding process and stable encoding quality are achieved.

CN122179559APending Publication Date: 2026-06-09MOORE THREADS TECH CO LTD
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Patent Information

Application Number
CN202610628864.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-09
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

Existing video coding methods have low accuracy in making coding parameter decisions for units with high texture complexity, resulting in low coding efficiency.

Method used

A subjective quality prediction model is used to train a machine learning model on sample image frames to obtain the encoding quality of multiple candidate encoding parameters. The target encoding parameter that meets the quality requirements is selected for encoding, thereby improving the accuracy and stability of the encoding process.

Benefits of technology

By using the evaluation criteria of the subjective quality prediction model, coding decision errors can be reduced, the accuracy and stability of the coding process can be improved, and the coding quality can be ensured to meet the evaluation requirements from the user's perspective.

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Abstract

The embodiment of the application discloses a kind of encoding method, device, encoder, medium and product, belong to video coding technique field.The encoding method includes: obtaining multiple candidate encoding parameters, candidate encoding parameters are used to indicate the encoding mode of current frame;Obtain the encoding quality corresponding to multiple candidate encoding parameters respectively by subjective quality prediction model, subjective quality prediction model is the machine learning model obtained by training sample image frame, sample image frame is labeled with reference encoding quality, reference encoding quality is labeled from subjective view, and reference encoding quality is used to express the data consistency before and after sample image frame encoding;From multiple candidate encoding parameters, obtain the target encoding parameter of the encoding quality that meets quality requirement;Output the code stream data of current frame encoding under target encoding parameter.Through subjective quality prediction model, the efficiency of obtaining the encoding mode adapted to current frame is improved, and the accuracy and stability of encoding process are improved.
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