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Full-reference screen video quality evaluation method based on spatial-temporal Gabor feature tensor

A technology of screen video and reference screen, which is applied in the field of full-reference screen video quality assessment based on spatio-temporal Gabor feature tensor, and can solve problems such as not fully considering the structure and statistical characteristics of screen video

Active Publication Date: 2020-08-07
HUAQIAO UNIVERSITY
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0004] Since most of the existing quality evaluation methods are designed for natural scene image videos, they do not fully consider the structure and statistical characteristics of screen videos.

Method used

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  • Full-reference screen video quality evaluation method based on spatial-temporal Gabor feature tensor
  • Full-reference screen video quality evaluation method based on spatial-temporal Gabor feature tensor
  • Full-reference screen video quality evaluation method based on spatial-temporal Gabor feature tensor

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Embodiment Construction

[0061] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0062] see figure 1 As shown, a full-reference screen video quality assessment method based on the spatio-temporal Gabor feature tensor, the specific steps are as follows:

[0063] 1) Input the reference screen video r and the distorted screen video d, and combine the reference screen video and the distorted screen video respectively along the time axis according to consecutive frames to obtain the reference screen video unit and the distorted screen video unit;

[0064] 2) Extract the spatio-temporal Gabor feature tensor of the reference screen video r respectively and the spatiotemporal Gabor feature tensor of the distorted screen video d Wherein, the spatio-temporal Gabor feature tensor of reference screen video r is extracted, and the steps are as follows:

[0065] 2.1a) Calculate the space-time Gabor feature tensor in the x direction...

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Abstract

The invention relates to a full-reference screen video quality evaluation method based on a spatial-temporal Gabor feature tensor. The full-reference screen video quality evaluation method comprises the following steps of: firstly, respectively giving reference and distorted screen video sequences, and applying a 3D-Gabor filter to the reference and video sequences to obtain a spatial-temporal feature tensor; secondly, calculating the spatial-temporal feature tensor similarity of the reference screen video and the distorted screen video; and finally, acquiring a quality score of the distortedscreen video by using a pooling strategy based on the spatial-temporal feature tensor. The full-reference screen video quality evaluation method provided by the invention is simple in calculation andcan accurately evaluate the screen video quality.

Description

technical field [0001] The present invention relates to the field of video processing, in particular to a full-reference screen video quality evaluation method based on the spatio-temporal Gabor feature tensor. Background technique [0002] With the vigorous development of cloud computing, mobile Internet and multimedia technology, screen video has been widely concerned and applied in various fields, such as online education, remote computing, video conferencing, game live broadcast and virtual desktop sharing, etc. Unlike natural scene video, screen video is composite visual content that includes non-continuous-tone areas directly generated or rendered by a computer, such as icons, diagrams, text, etc., and camera-generated continuous-tone areas, such as natural scene video clips Wait. Video processing is aimed at providing high-definition video subjective visual quality. However, like natural scene videos, screen videos will inevitably introduce various distortions durin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N17/00G06T7/00
CPCG06T7/0002G06T2207/10016G06T2207/30168H04N17/00
Inventor 曾焕强程姗陈婧侯军辉朱建清马凯光
Owner HUAQIAO UNIVERSITY
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