Measurement method for image Gaussian Blur

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...

AI Technical Summary

Problems solved by technology

[0012] 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 Corresponding gray value The extreme point can only be judged by the interpolation method, which largely affects the position of the starting point and end point of the edge, that is, the width of the image. This method can achieve a more correct image blurring measurement for images with a small blurring degree. However, for images with a large blur, the image blur cannot be accurately measured.

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