Encoder adaptive adjustment method based on subjective quality evaluation

Abstract

The invention relates to an encoder adaptive adjustment method based on subjective quality evaluation. The method comprises the following steps: step A, through analyzing influences exerted by encoding parameters and configuration conditions on a video stream code rate, establishing an HEVC encoder parameter model; step B, by use of subjective perception of a terminal user for received video quality, establishing a subjective QoE model integrally taking encoder arrangement and network loss factors into consideration; and step C, based on the established subjective QoE model, for video service of multiple users, constructing an adaptive adjustment algorithm maximizing total QoE of all the users under the condition of a limited channel capacity. Compared to the prior art, the method provided by the invention substantially improves user total satisfaction under the condition of multiple users, at the same time, supports resource distribution according to user priorities, and has great significance on improvement of system performance and optimization of network resource distribution.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to an encoder adaptive adjustment method based on subjective quality assessment. Background technique [0002] With the development of network transmission technology and video compression technology, end users expect higher quality video services. In order to obtain higher user satisfaction, Quality of Experience (QoE) was proposed by ITU-T in 2012 to describe the quality of service perceived by end users and gradually replace objective Quality of Service (QoS) indicators, which are used Network-based resource allocation and performance optimization. Generally speaking, QoE is affected by both application layer parameters (AQoS) and network layer parameters (NQoS) factors. [0003] Video service is one of the most important services in next generation network services. High Efficiency Video Coding (HEVC), as the latest video coding standard, can save 50% bandwidth...

AI Technical Summary

Problems solved by technology

[0004] There are two major problems in the current research work. One is that QoE is affected by both application layer parameters (AQoS) and network layer parameters (NQoS).

However, most of the current QoE modeling work for video services only examines the impact of application layer parameters and network parameters on video applications, and does not give a model for comprehensive consideration.

The second is QoE-based network optimization work, most of which use objective QoE, only by adjusting the transmission rate of the source, without considering the influence of encoder parameters

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