Full-reference-type image quality evaluation method based on Gabor weighted characteristics

Abstract

The invention relates to a full-reference-type image quality evaluation method based on Gabor weighted characteristics. Specific steps of the method are as follows: 1. inputting an distorted image and a reference image; 2.carrying out two-dimension Gabor conversion on the input distorted image and reference image so as to obtain Gabor factors; 3. forming a matrix through the Gabor factors of the distorted image and the reference image and carrying out principal component analysis on the matrix so as to obtain first and second principal component components; 4. forming principle component matrixes through the first and second principle component components of the distorted image and the reference image and calculating the similarities and similarity mean values of the principle component matrixes of the distorted image and the reference image; 5. carrying out weighed sum on the similarity mean values so as to obtain an objective evaluation score. The full-reference-type image quality evaluation method based on the Gabor weighted characteristics converts the images through adoption of Gabor conversion and PCA conversion and carries out weighted sum on the similarity mean values so as to obtain the objective evaluation score and thus the precision of the image quality evaluation is improved.

Description

(1).Technical field [0001] The invention belongs to the field of image processing, and relates to an image quality evaluation method, in particular to a full-reference image quality evaluation method based on Gabor weighted features. (2). Background technology [0002] Image quality evaluation method is a key issue in the field of image processing, and image quality evaluation can be divided into subjective image quality evaluation methods and objective image quality evaluation methods. The subjective evaluation method scores according to the observer's feelings. Although it is accurate, it has the disadvantages of high cost and time-consuming. The objective image quality evaluation method uses a calculation model to automatically predict the image quality, which is low in cost and time-consuming, and has good application value. . Objective image quality assessment methods can be divided into full-reference image quality assessment methods, semi-reference image quality asse...

AI Technical Summary

Problems solved by technology

[0003] The traditional full-reference image quality evaluation method (such as peak signal-to-noise ratio PSNR) uses the mean square error between the distorted image and the reference image as the basis for image evaluation. The calculation is simple, but it does not match the subjective visual characteristics of the human eye. Disadvantages, not widely used in practical situations

Aiming at the deficiencies of the traditional full-reference image quality evaluation method, many scholars have proposed improved methods, Wang Zhou (Z.Wang and A.C.Bovik, Image quality assessment: from error visibility to srtuctural similarity, IEEE Transaction on image processing, 13, 600- 612, 2004.) and others proposed a structural similarity (SSIM) method based on image structural similarity. This method uses the structural similarity of the main image to evaluate the quality of the image, but this method does not transform the image. Make full use of the frequency domain information contained in the image

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