Reference-free stereoscopic video quality objective evaluation method based on multi-view feature learning
A technology for objective quality evaluation and stereoscopic video, applied in the field of video processing, it can solve the problems of high cost, long time, and difficult application, and achieve the effect of high consistency, improved performance, and accurate and objective evaluation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2019-03-05
Smart Images

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Abstract
Description
technical field
[0001] The invention relates to the field of video processing, and more specifically relates to a method for objectively evaluating the quality of stereoscopic video without reference based on multi-view feature learning. Background technique
[0002] Since 3D can bring audiences a sense of three-dimensionality and a more realistic viewing experience, 3D video technology has attracted widespread attention from industrial product manufacturers and electronic product consumers. However, any link in the process of video acquisition, encoding compression, transmission, processing, and display may cause video distortion, resulting in a decrease in video quality. Therefore, the research on video quality evaluation is of great importance to promote the development of image and video processing technology. significance.
[0003] Stereoscopic video quality assessment methods are divided into two methods: subjective quality assessment and objective quality assessment....
Examples
Embodiment Construction
[0057] The present invention will be further described below in conjunction with the accompanying drawings.
[0058] The non-reference stereoscopic video quality objective evaluation method based on multi-view feature learning of the present invention utilizes the LBP operator to extract the characteristics of the influence of distortion on the spatial domain characteristics, uses the new three-step search method to extract the characteristics of the influence of distortion on the time domain characteristics of the video, and uses DCT Transform and extract the stereoscopic features of the video, and use the support vector machine (SVM) as a tool to train the extracted three-part features separately and obtain the quality scores of the three parts; finally weight the three-part scores as the final result of the stereoscopic video Quality score, so as to make a more comprehensive and accurate objective evaluation of stereoscopic video quality.
[0059] Such as Figure 1 to Figu...