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Image Quality Evaluation Method Based on Human Visual System

An image quality evaluation and human visual system technology, applied in the field of image quality evaluation based on the human visual system, can solve the problems of not considering the characteristics of natural images, insufficient application, and inability to predict the image quality of distortion types well, so as to save Economic cost and time cost, effect of avoiding experiments

Active Publication Date: 2022-05-10
朱苗
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method takes into account some of the characteristics of the human eye, the effect is not very good
At the same time, the existing structural similarity algorithms are not sufficiently applied to human visual characteristics, resulting in a problem of not very high subjective and objective consistency.
This method only roughly extracts the brightness, structure, and contrast information of two grayscale images based on experience, and then performs point multiplication on the three. It does not consider the characteristics of natural images, and cannot predict the image quality of certain types of distortion well. It is not detailed. Research on the human visual system does not have a good objective evaluation effect on noise pollution and blurred images

Method used

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  • Image Quality Evaluation Method Based on Human Visual System
  • Image Quality Evaluation Method Based on Human Visual System
  • Image Quality Evaluation Method Based on Human Visual System

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Experimental program
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Effect test

Embodiment 1

[0061] See image 3 , image 3 It is a schematic flowchart of an image quality evaluation method based on the human visual system provided by an embodiment of the present invention.

[0062] A method for evaluating image quality based on the human visual system, comprising the following steps:

[0063] (a) Obtain the original image and the distorted image;

[0064] (b) establishing a GLOP filtering model, filtering the original image and the distorted image according to the GLOP filtering model, obtaining the filtered original image and the filtered distorted image;

[0065] (c) obtaining structural similarity according to the filtered original image and the filtered distorted image;

[0066] (d) Obtaining an objective value of quality evaluation of the distorted image according to the structural similarity.

[0067] In this embodiment, the GLOP filtering model is added to smooth the original image and the distorted image, that is, the principle of the human visual system ...

Embodiment 2

[0071] see again image 3 , see also Figure 4 , Figure 4 It is an algorithm schematic diagram of an image quality evaluation method based on the human visual system provided by an embodiment of the present invention. In this embodiment, on the basis of the foregoing embodiments, a detailed description is focused on an algorithm based on the objective value of the image quality evaluation of the human visual system.

[0072] (S10) Acquiring the original image A and the distorted image B;

[0073] In this embodiment, the original image A and the corresponding distorted image B distorted due to pollution are obtained respectively.

[0074] (S20) Perform first preprocessing on the original image A and the distorted image B.

[0075] The process of the first pretreatment includes the following steps:

[0076] (S201) Convert the original image A and the distorted image B into grayscale images.

[0077] Because the algorithm of the structural similarity in the present inventi...

Embodiment 3

[0162] On the basis of the above-mentioned embodiments, this embodiment focuses on the method of evaluating the subjective and objective consistency of the objective value of the quality evaluation of the distorted image.

[0163] As early as 1974, the Video Quality Expert Group established an expert organization, which is mainly used to evaluate the performance of video quality evaluation algorithms. The experimental data used to evaluate the performance of the algorithm in this paper are all obtained from the LIVE database, which comes from the TEXAS Image Video Engineering Laboratory in the United States, and is used for image quality evaluation, and it is the second edition. There are 29 original images in this database, all of which are RGB color images with a resolution of 24 bits. These original images have undergone 4 different types of distortion, namely JPEG2000 and JPEG compression, white noise pollution (wn), Gaussian blur (gblur), and there are 683 distorted image...

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Abstract

The present invention relates to an image quality evaluation method based on the human visual system, comprising the following steps: (a) acquiring an original image and a distorted image; (b) establishing a GLOP filtering model, and performing an evaluation of the original image and the obtained image according to the GLOP filtering model Filter the distorted image to obtain the filtered original image and the filtered distorted image; (c) obtain the structural similarity according to the filtered original image and the filtered distorted image; (d) obtain the obtained structure according to the structural similarity The objective value of the quality evaluation of the distorted image. The embodiment of the present invention not only improves the subjective and objective consistency of images, but also improves the objective evaluation of distorted images.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to an image quality evaluation method based on a human visual system. Background technique [0002] With the wide application of digital image processing in satellite remote sensing, biomedicine, public security and other fields, people have higher and higher requirements for the effect of image quality evaluation methods. In recent years, image quality evaluation has become an important research topic in image information engineering. Therefore, it is of great practical significance to study the evaluation method of image quality. Although the traditional image quality evaluation method based on peak signal-to-noise ratio is simple in form and convenient in calculation, it has almost nothing to do with the human visual system, which often leads to inconsistent subjective and objective evaluation results. [0003] Such as figure 1 as shown, figure 1 It is a schematic ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/20024G06T2207/30168
Inventor 朱苗
Owner 朱苗
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