No-reference stereo image quality evaluation method based on a quality map generation network

A stereoscopic image and quality evaluation technology, which is applied in image analysis, image data processing, instruments, etc., can solve the problem of seldom considering model versatility, seldom considering stereoscopic images, left viewpoint and right viewpoint weight distribution affecting stereoscopic image quality, etc. question

Active Publication Date: 2019-06-11
ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0003] Most of the existing stereoscopic image quality evaluation methods cannot accurately judge the quality of stereoscopic images, and rarely consider the versatility of the model. They are all trained and tested on a database, and image saliency is

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  • No-reference stereo image quality evaluation method based on a quality map generation network
  • No-reference stereo image quality evaluation method based on a quality map generation network
  • No-reference stereo image quality evaluation method based on a quality map generation network

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Embodiment Construction

[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0036] A no-reference stereoscopic image quality evaluation method based on the quality map generation network proposed by the present invention, its overall realization block diagram is as follows figure 1 As shown, it includes two processes of training phase and testing phase;

[0037] The specific steps of the described training phase process are:

[0038] Step 1_1, select n wsz The original undistorted planar image is used to establish a set of distorted planar images under different distortion types and degrees of distortion, and the set of distorted planar images is used as a training set. The training set contains multiple distorted planar images. The i-th image in the training set The distorted plane image is denoted as {I dis,i (x',y')}, will {I dis,i (x',y')} The corresponding original undistorted plane image is denoted as {I re...

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Abstract

The invention discloses a no-reference stereo image quality evaluation method based on a quality map generation network. The method comprises the steps of in a training stage, constructing a quality map generation network, sequentially inputting normalized images of all distorted plane images in a training set into the quality map generation network, taking a corresponding quality map as supervision, and performing training to obtain an optimal quality map generation network model; Test phase, utilizing the optimal quality map to generate a network model to extract a left viewpoint image of the distorted stereo image to be evaluated; predicting quality maps of the normalized images of the right viewpoint image and the fused image respectively, acquiring respective salient feature maps, solving respective predicted quality scores according to the corresponding predicted quality map and the corresponding salient feature map, and fusing the three predicted quality scores to obtain a finalpredicted quality score; The method has the advantages that the influence of various characteristics of the stereoscopic image on the visual quality can be fully considered, so that the correlation between an objective evaluation result and binocular subjective perception can be improved.

Description

technical field [0001] The invention relates to an image quality evaluation technology, in particular to a no-reference stereo image quality evaluation method based on a quality map generation network. Background technique [0002] With the rapid development of stereoscopic image applications, many related stereoscopic image technologies and services have been introduced into people's daily life and many professional fields. Various distortions may occur during the collection, transmission, processing and display of stereoscopic images. Therefore, it is of great practical significance to establish a high-performance stereoscopic image quality evaluation method. Stereoscopic image quality evaluation can be divided into two ways: subjective evaluation and objective evaluation. The subjective evaluation is that people directly evaluate the stereoscopic image subjectively. Since the Human Visual System (HSV) is the final receiver of the stereoscopic image, the subjective evalu...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 周武杰张爽爽何成王海江邱薇薇陈芳妮张宇来楼宋江
Owner ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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