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Visual-saliency-based image quality evaluation method

An image quality evaluation and saliency technology, applied in the field of full-reference image quality evaluation based on visual saliency, can solve the problem of incomplete agreement of subjective visual evaluation

Inactive Publication Date: 2016-08-03
TIANJIN UNIV
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Problems solved by technology

Traditional image fidelity quantitative indicators mainly include peak signal-to-noise ratio (peak-to-noiseratio, PSNR), root mean square error (meansquarederror, MSE), etc., but when targeting multi-scale or multiple distortion situations, these indicators It is not completely consistent with human subjective visual evaluation, so many complex IQA models have been proposed for image quality evaluation in recent years

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Embodiment Construction

[0034] The random area quality evaluation proposed by the present invention is improved on the basis of the traditional evaluation method, and its algorithm is as follows: figure 1 shown. (1) In order to improve the performance of the evaluation method and the visual saliency algorithm, the image color space is converted to meet the requirement that the same chromaticity change leads to the same quality change. First, the reference image I R and distorted image I D Gaussian filtering is performed, and then the filtered image RGB is converted into the Lab color space, because the Lab color space is very similar to human psychological vision. The conversion method is as follows:

[0035] L=0.2126×R+0.7152×G+0.0722×B

[0036] a=1.4749×(0.2213×R-0.3390×G+0.1177×B)+128

[0037] b=0.6245×(0.1949×R+0.6057×G-0.8006×B)+128

[0038] The value ranges of RGB and Lab are both [0,255]. Thus, the three channels L of the two images are respectively obtained R ,a R ,b R and L D ,a ...

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Abstract

The invention, which relates to the digital image processing field, provides a visual-saliency-based random image region quality evaluation strategy, so that an evaluation result meets the subjective perception of the human being. According to the technical scheme, the method comprises: (1), Gaussian filtering is carried out on a reference image IR and a distorted image ID respectively and the filtered image RGBs are converted into Lab color space units; (2), for different image sizes r*c, N windows with random sizes are generated randomly; (3), visual saliency calculation is carried out the reference image and the distorted image respectively by using a visual-saliency extraction algorithm and a visual saliency similarity matrix in each random window is obtained; (4), weighting and integration are carried out on the obtained similarity matrixes of all random windows. The method is mainly applied to an image processing occasion.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to a full-reference image quality evaluation method based on visual salience for random regions. Background technique [0002] With the development of digital image applications in various fields, Image Quality Assessment (IQA) has been paid more and more attention in the fields of image processing analysis, data compression, storage and communication transmission. It is an important index to measure image quality. Image quality evaluation methods can generally be divided into two types: subjective quality evaluation methods based on human eyes, and objective quality evaluation methods based on algorithms that simulate human vision. Although image quality evaluation ultimately takes human subjective evaluation as the fundamental criterion, this evaluation method is costly and time-consuming and is not easy to implement in a real-time system. Therefore, an objective quality ev...

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Application Information

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IPC IPC(8): G06T7/00G06T7/40
CPCG06T7/0002G06T2207/10004G06T2207/30168
Inventor 史再峰陈可鑫庞科曹清洁王晶波张嘉平
Owner TIANJIN UNIV
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