Full-reference image quality assessment method based on mutual information of Gabor features (MIGF)

An image quality evaluation and reference image technology, applied in the field of image processing, can solve the problems of human visual system that does not take into account the correlation of pixels, subjective perception does not meet, etc.

Inactive Publication Date: 2012-06-13
ZHEJIANG UNIV
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Problems solved by technology

Although these indicators are relatively simple and intuitive, they only make pure mathematical statistics on the error between pixels, without taking into account the correlation between pixels and the perceptual characteristics of the Human Visual System (HVS), so in some cases the evaluation The results do not match the subjective feelings of human beings

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  • Full-reference image quality assessment method based on mutual information of Gabor features (MIGF)
  • Full-reference image quality assessment method based on mutual information of Gabor features (MIGF)
  • Full-reference image quality assessment method based on mutual information of Gabor features (MIGF)

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Embodiment Construction

[0043] The method of the present invention will be further described below in conjunction with the accompanying drawings.

[0044] Such as figure 1 Shown is the method flow process of the present invention, and concrete implementation steps are as follows:

[0045] Step (1). Input a reference image and a distorted image;

[0046] Step (2). Establish a group of two-dimensional Gabor filters , where the number of two-dimensional Gabor filters is , is a positive integer, ; When the reference image and the distorted image are subjected to the two-dimensional Gabor filter After processing, the Gabor feature of the obtained reference image is , the Gabor feature of the distorted image is ;

[0047] Create a set of two-dimensional Gabor filters Specific steps are as follows:

[0048] Pick = 3 scales and = 4 directions, then =12,

[0049] For the first two-dimensional Gabor filter , which is defined as:

[0050]

[0051] in is the two-dimensional Gab...

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Abstract

The invention discloses a full-reference image quality assessment method based on mutual information of Gabor features (MIGF), belonging to the field of image processing. The method specifically comprises the following steps: (I) inputting a reference image and a distorted image; (II) filtering the reference image and the distorted image with two-dimensional Gabor filters respectively to extract Gabor features; (III) building probability distribution functions respectively and computing probability distribution of each pixel and joint probability distribution of the filtered images; (IV) computing the MIGF of the reference image and the distorted image; and (V) building an image quality assessment function MIGF to assess the image quality. The method has the following beneficial effects: the two-dimensional Gabor filters are utilized to extract visual features; the image quality assessment function is built through the mutual information of the reference image and the distorted image; and the assessment results conform to subjective recognition of human visions.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a full-reference image quality evaluation method based on Gabor feature mutual information. Background technique [0002] In the process of image processing and compression, images are prone to distortion, so how to accurately evaluate image quality has become a research hotspot in the field of image processing and compression. Objective image quality evaluation methods are mainly divided into: full-reference image quality evaluation (full-reference, FR), which needs to use reference images (ie original images) to evaluate the quality score of distorted images; no-reference image quality evaluation (no-reference, NR), that is, it only needs to use the distorted image to obtain its quality score, and does not need the reference image as a reference; partial reference image quality evaluation (reduced-reference, RR), this method does not need a reference image, but needs t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N17/00
Inventor 丁勇谢鹏宇张渊曲东昌林冬阳雷李楠林凯旋
Owner ZHEJIANG UNIV
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