HEVC (High Efficiency Video Coding) decoded video subjective quality evaluation method

Abstract

The invention discloses an HEVC (High Efficiency Video Coding) decoded video subjective quality evaluation method. The method comprises the steps of firstly calculating the average objective quality of decoded video, then extracting the movement trend of an object in images so as to be used for showing movement of the object in the video by being combined with a coding frame rate, and finally calculating influences imposed on the video subjective quality by the image resolution. An HEVC decoded video subjective quality evaluation model is built based on the above three steps so as to quantitatively calculate the subjective quality of the decoded video. The HEVC decoded video subjective quality evaluation method provided by the invention more conforms to characteristics of a human visual system, and evaluation for the quality of the decoded video is more capable of reflecting subjective visual feelings brought to people by the decoded video when being played. The evaluation model not only can be used for evaluating the subjective quality of stored video, but also can be applied to a real-time video application.

Description

technical field [0001] The invention belongs to the field of multimedia encoding and decoding, and in particular relates to a subjective quality evaluation method of HEVC decoding video. Background technique [0002] As human beings enter the information age, digital video technology has developed rapidly. Digital video has the advantages of being easy for computer processing, easy to encrypt, and suitable for long-distance transmission. Its application scenarios are constantly expanding, and it is playing an increasingly important role in the fields of industrial and agricultural production, military reconnaissance, daily work, and leisure and entertainment. However, due to the huge amount of raw video data acquired by video capture equipment, especially with the emergence and wide application of high-definition and ultra-high-definition video, the amount of raw video data is even larger, and the available storage resources and transmission resources are always limited. , ...

AI Technical Summary

Problems solved by technology

[0010] Although the above two subjective quality evaluation methods of decoded video can achieve good results, the observer's knowledge level, professional field, personal preference and number of participants will directly affect the final evaluation results, resulting in a lack of objectivity in the evaluation results.

Moreover, this evaluation method takes a long time and is not suitable for video applications that require high real-time performance, such as video conferencing, live video broadcasting, remote video monitoring, etc.

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