A video coding rate control method and device, electronic equipment and storage medium

By using edge computing servers to dynamically adjust the quantization parameters of video encoding through parameter fitting models and perceptual quality assessment, the problem of video encoding efficiency and quality under different network environments and devices is solved, achieving more efficient video compression.

CN119946264BActive Publication Date: 2026-07-03RUIJIE NETWORKS CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
RUIJIE NETWORKS CO LTD
Filing Date
2023-11-01
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

In the video encoding process, how can we dynamically adjust quantization parameters to achieve more efficient video compression while ensuring video quality, especially under the needs of different network environments and devices, to meet the bitrate requirements of different business scenarios?

Method used

By dynamically adjusting the quantization parameters of video encoding through an edge computing server, and using a parameter fitting model combined with image complexity, motion estimation, and perceptual quality assessment models, the optimal set of quantization parameters is predicted and selected to encode the video stream.

Benefits of technology

It improves video encoding efficiency, ensures video quality, and dynamically adjusts quantization parameters to adapt to the needs of different network environments and devices, thereby improving video compression efficiency.

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Abstract

This application discloses a video encoding bitrate control method, apparatus, electronic device, and storage medium. The method includes: acquiring the current image frame of a video stream to be processed according to a preset time period; determining each first target region and the image complexity of each first target region of the current image frame according to a preset algorithm; inputting each first target region, the image complexity of each first target region, the target quantization parameter set of the previous image frame, the bitrate of the previous image frame, and the perceived image quality evaluation value of the previous image frame into a parameter fitting model to obtain a preset number of quantization parameter sets for the current image frames; determining the target quantization parameter set of the current image frame based on the preset number of quantization parameter sets of the current image frames and the perceived quality evaluation model; and encoding the current image frame and image frames in the next time period according to the target quantization parameter set of the current image frame.
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