Non-local means filtering method for speckle noise pollution image

Abstract

The invention discloses a non-local means filtering method for a speckle noise pollution image. The method comprises that iterative computation of a neurons firing state image series of the speckle noise pollution image is conducted through a pulse transmission cortex model, a Renyi entropy vector is extracted by the neurons firing state image series, and non-local means filtering is conducted on the speckle noise pollution image based on the Renyi entropy vector, so that a denoised gray value is obtained. By the aid of the method, rotation invariance, translation invariance and scaling invariance can be extracted from the image containing speckle noise, the method can use more image information for denoising than traditional methods, besides, the similarity between two image pixel blocks can be calculated reasonably, image noise can be suppressed significantly, and the peak signal-to-noise ratio of the image can be improved, so that detailed information of the image can be effectively protected.

Description

technical field [0001] The invention belongs to the field of image denoising enhancement, and more specifically relates to a non-local mean value filtering method for speckle noise polluted images. Background technique [0002] Image filtering technology is one of the image processing technologies that has been concerned and developed rapidly in recent years, and the removal of speckle noise in images is one of the research hotspots, especially in the field of medical image processing. Image filtering, that is, to suppress the noise of the target image under the condition of retaining the image details as much as possible, is an indispensable operation in image preprocessing, and its processing effect will directly affect the effectiveness and effectiveness of subsequent image processing and analysis. reliability. [0003] The speckle noise in the image not only reduces the picture quality of the image, but also seriously affects the automatic segmentation, classification, ...

AI Technical Summary

Problems solved by technology

After consulting the existing literature, the Chinese patent SAR image non-local mean speckle removal method (patent number: 200910219211.3) discloses a SAR image non-local mean speckle removal method, which can overcome the existing non-local mean speckle reduction algorithm. The problem of inaccurate calculation of image block distance

[0005] However, the existing non-local mean filtering methods for speckle noise polluted images only consider the image self-similarity from the perspective of translation invariance, but ignore the rotation and scale invariance in the image, so it is difficult to effectively protect the complex details and texture information

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