Reference-free evaluation method for multi-distortion image quality

A technology of distorted images and evaluation methods, applied in image enhancement, image analysis, image data processing, etc.

Active Publication Date: 2018-05-18
CHINA UNIV OF MINING & TECH
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  • Reference-free evaluation method for multi-distortion image quality
  • Reference-free evaluation method for multi-distortion image quality
  • Reference-free evaluation method for multi-distortion image quality

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[0079] The present invention will be further described below in conjunction with the accompanying drawings.

[0080] figure 1 Shown is the principle flowchart of the present invention, and the present invention mainly comprises the following steps:

[0081] 1. Obtain M original multi-distortion images, and perform steps (1-1) to (1-3) for each original multi-distortion image

[0082] (1-1) downsampling: record any original multi-distortion image as I 0 , for image I 0 Carry out n times of down-sampling respectively to obtain n down-sampled images, and record I i For the i-th downsampled image, i∈[1,2,…,n]; the image I 0 to I n into image I 0 sample set;

[0083] (1-2) Carry out two-order structural feature extraction to each image in the sample collection, obtain the first-order structural distortion feature and the second-order structural distortion feature of each image;

[0084](1-3) performing non-local similarity statistical feature extraction on each image in the...

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Abstract

The invention provides a reference-free evaluation method for multi-distortion image quality. The method is an evaluation method based on bi-order structural distortion and non-local statistics. The method comprises the steps that first, downsampling is performed on a multi-distortion image to obtain multiple resolution images, and bi-order structural features of each resolution image are extracted and used for evaluating structural distortion in the image, wherein all the structural features form a first group of quality evaluation features; second, non-local similarity statistical features of each resolution image are extracted, and the features are used as a second group of quality evaluation features; and last, the two groups of features of the image are used as input, and a random forest is utilized to train a quality evaluation model of the multi-distortion image. The performance of the method is obviously superior to that of an existing reference-free image quality evaluation method, and the method has good cross-base performance and high extensibility.

Description

technical field [0001] The invention relates to the field of image quality evaluation, in particular to a no-reference evaluation method for multi-distortion image quality. Background technique [0002] Image quality evaluation is widely used in the field of image processing and practical applications [1]. At present, there are already a large number of image quality evaluation methods. Image quality evaluation methods can be divided into subjective image quality evaluation methods and objective image quality evaluation methods. The subjective quality evaluation method refers to judging the quality of an image by human eyes. This method has high accuracy, but it is time-consuming, labor-intensive, and costly, especially when there are a large number of images that need to be evaluated for quality, it has relatively large defects. The objective image quality evaluation method refers to evaluating the image quality score by designing a mathematical model. The objective qua...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06T7/12
CPCG06T5/008G06T7/0002G06T2207/20021G06T2207/30168G06T7/12
Inventor 周玉李雷达卢兆林
Owner CHINA UNIV OF MINING & TECH
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