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A Measuring Method of Image Gaussian Blur

A Gaussian blur and fuzziness technology, applied in the field of image processing, can solve the problem of inaccurate measurement of image blur

Inactive Publication Date: 2016-05-25
XIHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0011] In this method, the direction of edge expansion greatly affects the position of the starting point and end point of the edge, especially for some directions with the fastest grayscale change, for example, the gradient direction is 15 degrees. Since there are only sub-pixel points in the gradient direction, there is no The corresponding gray value can only be judged by the interpolation method, which greatly affects the position of the starting point and the ending point of the edge, that is, the width of the image. Image blurriness measurement, but for images with large blurriness, the image blurriness cannot be accurately measured

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  • A Measuring Method of Image Gaussian Blur

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Experimental program
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Effect test

Embodiment 1

[0100] Embodiment one: if image 3 , Figure 4 , Figure 5 , Figure 6 As shown, the four images are grayscale images that have undergone decolorization preprocessing. image 3 Represents the original image blurred by a Gaussian blur standard deviation σ of 3.2, Figure 4 Represents the original image blurred by a Gaussian blur standard deviation σ of 3.6, Figure 5 Denotes the original image blurred by a Gaussian blur standard deviation σ of 4.0, Figure 6 Represents the original image blurred by the Gaussian blur standard deviation σ being 4.4, and the above grayscale images with different blur levels are used as the original images for evaluating the same image with different blur levels by the method of the present invention. By using the Sobel horizontal and vertical matrices for the four original grayscale images to obtain the horizontal and vertical gradients of the image, and then the square of the gradient amplitude is equal to the sum of the square of the horizo...

Embodiment 2

[0103] Embodiment two: if image 3 , Figure 23 , Figure 24 , Figure 25 , Figure 39 and Figure 40 As shown, the four images are grayscale images that have undergone decolorization preprocessing. image 3 Represents the "building" original image blurred by a Gaussian blur standard deviation σ of 3.2, Figure 23 Represents the "paintedhouse" original image blurred by a Gaussian blur standard deviation σ of 3.6, Figure 24 Represents the "Woman" original image blurred by a Gaussian blur standard deviation σ of 4.0, Figure 25 Represents the "boat" original image that is blurred by the Gaussian blur standard deviation σ being 4.4, and the above grayscale images of different blurs are used as the original images of the method of the present invention to evaluate the different blurs of different image contents. By using the Sobel horizontal and vertical matrices for the four original grayscale images to obtain the horizontal and vertical gradients of the image, and then t...

Embodiment 3

[0107] Embodiment three: as Figure 39 , Figure 40 As shown, take the four grayscale images of "building", "paintedhouse", "Woman", and "boat" that have undergone decolorization preprocessing, and blur the four grayscale images with a Gaussian blur standard deviation σ of 0.8 For processing, the above grayscale image with the same blur degree is used as the original image for evaluating the same blur degree of different image contents by the method of the present invention. By using the Sobel horizontal and vertical matrices to obtain the horizontal and vertical gradients of the four original grayscale images, and then the square of the gradient amplitude is equal to the sum of the square of the horizontal gradient plus the square of the vertical gradient, the four original gray images are respectively obtained. Gradient-magnitude map of the degree map. Next, the arc tangent function is equal to the vertical gradient value divided by the horizontal gradient value, and the g...

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Abstract

The invention discloses a measurement method for image Gaussian Blur. The method is that the edge width of a Gaussian Blur image acts as a parameter for judging the image blurring degree. The implementation includes the steps of acquiring a grayscale of an image; acquiring a gradient magnitude diagram and a gradient direction angle of the grayscale; constructing a multi-scale and multi-direction Gaussian-Laplace filter; acquiring an energy diagram and a scale diagram correspondingly by carrying out convolution on the gradient magnitude diagram and the multi-scale and multi-angle Gaussian-Laplace filter; determining the position of an edge point through acquiring the position of a maximum value of each pixel on the energy diagram in the gradient direction; and finally acquiring the edge width of the original grayscale through calculation, thereby realizing measurement of the image Gaussian Blur. According to the method disclosed by the embodiment of the invention, the ratio between the increasing rate of the edge width acquired according to the method and the increasing rate of the blurring degree maintains certain stability, thereby avoiding the circumstance that an error occurs in a traditional evaluation method.

Description

technical field [0001] The invention belongs to the field of image processing and discloses a measurement method for image Gaussian blur. Background technique [0002] An image is a similar, vivid description or portrait of an objective object, and is the most commonly used information carrier in human social activities. With the development of modern science and technology, images are widely used in all walks of life, and even play a decisive role in some specific fields. Therefore, distinguishing the quality of images and determining the degree of blurred images have an important impact on social production and life. Image blur is one of the important indicators to measure the quality of digital images. Image quality assessment methods can be divided into full reference, weak reference, and no reference from the classification of reference sources. Full reference means that the corresponding result image is compared with the original image, weak reference means that part...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 裴峥罗晓晖刘晶江莉彭宏高志升贾年刘志才
Owner XIHUA UNIV
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