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This paper presents an image denoising method based on bilateral filtering and non-local means. The non-local region texture or structure of the image has the characteristics of repetition, which can be used to effectively preserve the edge and detail of the image. And compared with classical methods, bilateral filtering method has a better performance in denosing for the reason that the weight includes the geometric closeness factor and the intensity similarity factor. We combine the geometric closeness factor with the weight of non-local means, and construct a new weight. Experimental results show that the modified algorithm can achieve better performance. And it can protect the image detail and structure information better.
This paper presents an image denoising method based on bilateral filtering and non-local means. The non-local region texture or structure of the image has the characteristics of repetition, which can be used effectively with the edge and detail of the image. And Compared with classical methods, the bilateral filtering method has a better performance in denosing for the reason that the weight that the geometric closeness factor and the intensity similarity factor. The combination closeness factor with the weight of non-local means, and constructing a new weight. Experimental results show that the modified algorithm can achieve better performance. And it can protect the image detail and structure information better.