Hybrid image filtering method based on target scale

Abstract

The invention relates to a hybrid image filtering method based on target scale, which is mainly used for self-adaptive median filtering and anisotropic diffusion. The method is characterized in that: first anisotropic diffusion is carried out to a processed image, thereby inhibiting most noise other than pulse noise; then the target scale of all pixels of the diffused image are calculated; and finally the calculated target scale carries out self-adaptive median filtering to the diffused image so as to remove the rest pulse noise after diffusion and obtain the final result. The method can remove the noise of images with various gray levels, and simultaneously keeps the details of the images while removing the noise.

Description

Technical field [0001] The invention relates to a mixed image filtering method based on a target scale, in particular to a mixed image filtering method based on an adaptive median filter and anisotropic diffusion based on a target scale, which can be applied to various image preprocessing systems. Background technique [0002] Affected by factors such as hardware, environment, and human factors, there is always noise in the image, which affects the real situation of the image details to a large extent and reduces the image quality. In order to improve image quality and improve the effectiveness and reliability of subsequent processing such as image segmentation, feature extraction, and target recognition, filters must be used to remove interference noise in images. [0003] Because the traditional linear image filtering method cannot consider the local characteristics of the image and has no adaptive function, it always blurs the edge of the image while filtering the noise. ...

AI Technical Summary

Problems solved by technology

For the defect of anisotropic diffusion, there are two existing improvement methods: first, the anisotropic diffusion itself is improved so that it can remove impulse noise, but the computational complexity of the improved method has increased a lot, and the calculation Second, after anisotropic diffusion, median filtering is added to remove impulse noise, but none of the existing median filters can intelligently identify which pixels are impulse noise, and they often affect the entire image Filtering is performed, resulting in unnecessary loss of detail

Therefore, it is necessary to find a simple and effective filtering method that can protect the original details of the image to the greatest extent to make up for the defect that anisotropic diffusion cannot effectively suppress impulse noise.

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