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Non-reference screen image quality evaluation method based on global information.

A technology of image quality evaluation and reference screen, applied in the field of image quality evaluation

Inactive Publication Date: 2017-10-20
ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0005] The existing general-purpose no-reference image quality evaluation methods are mainly aimed at general images, and there are relatively few studies on special images (such as screen images). Since screen images contain text, graphics, and images, etc., the general No-reference evaluation methods are more challenging

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Embodiment Construction

[0021] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0022] A no-reference screen image quality evaluation method based on global information proposed by the present invention, its overall realization block diagram is as follows figure 1 As shown, it includes the following steps:

[0023] Step ①: Let {I d (i,j)} represents the distorted screen image to be evaluated, where 1≤i≤W, 1≤j≤H, W represents {I d The width of (i,j)}, H means {I d (i,j)} height, I d (i,j) means {I d The pixel value of the pixel whose coordinate position is (i, j) in (i, j)}.

[0024] Step ②: For {I d (i,j)} implement Gabor filtering to get {I d (i,j)} Gabor magnitude images and Gabor phase images at S different scales and T different directions, the {I d (i,j)} The Gabor magnitude image and Gabor phase image at the s scale and the t direction are correspondingly denoted as and Among them, S>1, T>1, 1≤s≤S, 1≤t≤T...

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Abstract

The invention discloses a non-reference screen image quality evaluation method based on global information. According to the method, Gabor filtering is implemented on a distorted screen image to obtain Gabor amplitude images and Gabor phase images in multiple scales and multiple directions; CLBP (Completed Local Binary Pttern) operation is used to process the Gabor amplitude images in the multiple scales and the multiple directions to obtain CLBP feature images; LPQ (Local Phase Quantization) operation is used to process the Gabor phase images in the multiple scales and the multiple directions to obtain LPQ feature images; joint probability function values of the CLBP feature images and the corresponding LPQ feature images are calculated; then respective conditional probability statistic feature vectors of the CLBP feature images and the LPQ feature images are acquired; and finally, support vector regression (SVR) technology is utilized to predict and obtain an objective quality evaluation prediction value of the distorted screen image. The method has the advantages that influences of a global information change on visual quality can be fully taken into account, and thus correlation between an objective evaluation result and a subjective perception can be improved.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to a global information-based no-reference screen image quality evaluation method. Background technique [0002] Image is an important way for human beings to obtain information. Image quality indicates the ability of image to provide information to people or equipment, and is directly related to the adequacy and accuracy of the information obtained. However, in the process of image acquisition, processing, transmission and storage, due to various factors, there will inevitably be degradation problems, which brings great difficulties to information acquisition or post-processing of images. Therefore, it is very important to establish an effective image quality evaluation mechanism. For example, it can be used for performance comparison and parameter selection of various algorithms in image denoising, image fusion and other processing processes; it can be used to guide the entire...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/44
CPCG06T7/0002G06T7/44G06T2207/30168
Inventor 周武杰邱薇薇周扬赵颖何成迟梁陈芳妮吴茗蔚葛丁飞金国英孙丽慧陈寿法郑卫红李鑫吴洁雯王昕峰施祥
Owner ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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