Method for reducing image noise and enhancing image

Abstract

The invention relates to a method for reducing noise of an image and intensifying the image, comprising the following steps that: (1) the coordinate and a grey level value of each pixel point of the image are read; (2) the whole image is traversed, an improved image noise reducing algorithm is adopted to calculate each pixel point so as to obtain a novel pixel value after the noise reduction; (3) the novel pixel value after the noise reduction is adopted to replace the value of each pixel of the prior image so as to obtain the image after the noise is reduced; (4) the image after the noise reduction is traversed, an improved Laplacian operator enhancing algorithm is adopted to calculate each pixel point so as to obtain a novel enhanced pixel value; and (5) a novel enhanced pixel value is adopted to replace the prior pixel value so as to obtain the finally enhanced image. The method performs the noise reduction and enhancement on the image by the improved image noise reduction algorithm and the improved Laplacian operator enhancing algorithm, has good image processing effect and meets the monitoring requirement.

Description

technical field [0001] The present invention relates to an image processing technology, in particular to a method for image noise reduction and image enhancement Background technique [0002] The video surveillance system is a new type of surveillance system that uses digital video processing technology as the core and comprehensively utilizes various technologies such as photoelectric sensors, computer networks, automatic control, and artificial intelligence. The video sent back by the monitoring system obtains the actual situation of the scene, and the high video image quality is especially beneficial to the monitoring personnel to find out the problems in the monitoring site in time and deal with them in time to ensure the safety of personnel and property. In the process of image acquisition, the video may be affected due to the limitation of the performance of the acquisition equipment, the interference of external signals during transmission, and the distortion in the d...

AI Technical Summary

Problems solved by technology

[0005] 2. The enhancement algorithm of the Laplacian operator extracts the information of the image according to the speed of change between pixels in the image. The algorithm believes that if the data of adjacent pixels changes rapidly, this change indicates that the pixel is at the edge of the image. By further strengthening the difference between adjacent pixel data, the edge will be sharper and the image will be enhanced, but the coefficient of the traditional Laplacian operator is fixed, and the strength of enhancement cannot be controlled;

[0006] 3. In the process of combining the other two, the purpose of the mean value filter itself is to reduce noise, so as to ensure that the noise will not be highlighted in the process of subsequent image enhancement, but due to the defects of the mean value filter itself, the noise reduction At the same time, superimposition occurs between pixels in the image, which is easy to lose a lot of information, and the image becomes blurred, which is not conducive to subsequent enhancement. Therefore, the effect of image enhancement is often not ideal, and the loss of image information due to mean filtering ( blur) is irreparable for subsequent enhancements

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