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No-reference image objective quality evaluation method based on structural distortion

A reference image, objective quality technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problem of not being able to obtain the original image, and achieve the effect of improving correlation

Active Publication Date: 2017-05-17
嘉兴智旭信息科技有限公司
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Problems solved by technology

Objective evaluation methods can be divided into three categories: full-reference image quality evaluation methods, semi-reference image quality evaluation methods, and no-reference image quality evaluation methods. Therefore, the research of no-reference image quality evaluation method is more practical

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  • No-reference image objective quality evaluation method based on structural distortion
  • No-reference image objective quality evaluation method based on structural distortion

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Embodiment Construction

[0030] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0031] A method for evaluating the objective quality of an image without reference based on structural distortion proposed by the present invention, its overall realization block diagram is as follows figure 1 As shown, it includes the following steps:

[0032] ① make {I d (i,j)} represents the distorted 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)}.

[0033] ② Utilize the existing eight filters in different directions to respectively pair {I d (i,j)} implements first-order filtering to get {I d (i,j)} first-order filtered images in eight different directions, the {I d (i,j)} The first-order filtered image in the direction of θ is denoted as Among them, the eight filters in d...

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Abstract

The present invention discloses a no-reference image objective quality evaluation method based on the structural distortion. The method comprises: obtaining first-order filtering images at eight different directions and without the direction of a distorted image to be estimated, and obtaining the maximum value images of the first-order filtering images; obtaining second-order filtering images at eight different directions and without the direction of the distorted image to be estimated, and obtaining the maximum value images of the second-order filtering images; obtaining the maximum value images of the first-order filtering images, the second-order filtering images at eight different directions and without the direction of the distorted image to be estimated and each local mode feature image of the maximum value image of the second-order filtering images to obtain each histogram statistic feature vectors; and testing all the histogram statistic feature vectors according to the support vector regression training models obtained according to the construction, and predicting and obtaining an objective quality evaluation value. The no-reference image objective quality evaluation method based on the structural distortion can effectively improve the correlation between the objective evaluation result and the subjective perception.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to an objective quality evaluation method based on structure distortion without reference image. 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 gu...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00
CPCG06T7/0002G06T2207/30168G06T5/73
Inventor 周武杰顾鹏笠张爽爽潘婷蔡星宇邱薇薇周扬赵颖陈芳妮陈寿法
Owner 嘉兴智旭信息科技有限公司
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