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Pixel type based objective assessment method of image quality by utilizing structural similarity

An objective evaluation method and technology of image quality, applied in image analysis, image data processing, instruments, etc., can solve problems such as lack of stability, poor effect, and no consideration of human eyes.

Inactive Publication Date: 2011-02-16
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it simply measures the grayscale difference between images or the relationship between signal and noise, and lacks stability under different image degradation conditions.
[0009] The newer and best algorithm is the SSIM (Structural Similarity) algorithm proposed by Wang Zhou et al. in 2004. It takes into account that the human eye is most concerned about the priori of the structural shape of the scene, so it has achieved good results, but its effect on the degree of blur Slightly larger, slightly louder, and slightly more ringing ripple image evaluation seems powerless
[0010] The traditional method calculates and processes all the pixels of the image with equal weights, without considering the interest of the human eye in different areas of the pixels, so the effect is often poor

Method used

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  • Pixel type based objective assessment method of image quality by utilizing structural similarity
  • Pixel type based objective assessment method of image quality by utilizing structural similarity
  • Pixel type based objective assessment method of image quality by utilizing structural similarity

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] The flow chart of image processing by the evaluation method of the present invention is as follows: figure 1 As shown, the evaluation value of the image quality can be obtained by inputting the reference image and the evaluation image. by Figure 2a As a reference to Figure I and Figure 2b As an example of the evaluation chart f, the process of the evaluation method of the present invention is described in detail:

[0073] (1) Obtain the information graph RWM with different weights of different pixel area types in the image:

[0074] Will Figure 2a shown in reference figure I and Figure 2b The evaluation graph f shown in the input;

[0075] Calculate the gradient G of the reference image I using the canny method I (x, y), and at the same time obtain two thresholds t1 and t2 that represent the strong and weak boundaries of the image gradient value, t1>t2; also use the canny method to obtain the gradient G of the evaluation map f (the final image to be evaluated)...

Embodiment 2

[0104] According to the same method in Example 1, respectively Figure 3a~3h make an evaluation, Figure 3a~3h A set of grayscale images (reference image and different degradation form images) shown is the reference image used in the experiment ( Figure 3a ) and evaluation graph ( Figure 3b~3h ), and the evaluation results are shown in Table 1. in Figure 3a Figure 3a For reference figure, Figure 3b is the mean shift plot, Figure 3c For comparison stretching diagram, Figure 3d is the salt and pepper noise map, Figure 3e is the multiplicative speckle noise map, Figure 3f is additive Gaussian noise, Figure 3g is the fuzzy graph, Figure 3h Compressed image for JPEG. The larger the W-GSSIM evaluation value in Table 1, the better the image quality. The reference figure is Figure 3(a); from the test results in Table 1, it can be seen that the evaluation method of the present invention is basically consistent with human observation.

[0105] Table 1

[0106] ...

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Abstract

The invention discloses a pixel type based assessment method of image quality by utilizing structural similarity, comprising the following steps: (1) computing gradients of the reference map and the assessment map by the Canny method, simultaneously obtaining two thresholds representing the strong and weak boundaries of the image gradient values, dividing each pixel position in the image into marginal, texture and flat regions and establishing the regional weight map (RWM) with different weights in different pixel region types; (2) comparing the brightness, contrast and gradient structural similarity of the reference map and the assessment map to obtain the gradient structural similarity (GSSIM) index; and (3) carrying out point multiplication on the RWM and the GSSIM obtained in the steps (1) and (2) to obtain the degeneracy information index map with different weights in different pixel regions and obtaining the mean of the map to obtain the assessment value for assessing the image quality. The method can be widely applied to each stage of image processing, can rapidly give the specific index value for measuring the image quality and is high in accuracy and strong in practicability.

Description

technical field [0001] The invention relates to the technical field of computer image processing, in particular to an objective evaluation method of image quality based on gradient structure similarity of pixel type. Background technique [0002] Images are obtained by observing the objective world in different forms and means with various observation systems, and can directly or indirectly act on the human eye to produce visual entities. About 75% of the information that humans obtain from the outside world is obtained from images, which not only shows the huge amount of image information, but also shows that humans have a high utilization rate of image information. With the development of signal processing theory and computer science and technology, image engineering has also become a subject with rich content and rapid development. An image (processing and analysis) system includes image acquisition, display, storage, communication, processing and analysis. It is widely...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 赵巨峰冯华君徐之海李奇
Owner ZHEJIANG UNIV
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