Image Denoising via Combination Anisotropic Diffusion and Bilateral Filtering

M. Zeinali, S. Saryazdi, Hossein Khodabakhshi Rafsanjani
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引用次数: 3

Abstract

In this paper we propose a new image denoising technique based on combination of nonlinear diffusion and bilateral filtering. The proposed algorithm uses Weighted Local Variance (WLV) of the residual image to determine the texture and fine details. These regions are denoised by bilateral filtering and then, are returned to the image denoised by P-M method. In fact, the WLV have a controlling role in amount of this combination. Denoising the residual image and adding it to the primary denoised image is the main novel idea of this paper. Experimental results confirm this image denoising approach is more efficient than nonlinear diffusion and the bilateral filtering while each algorithm accomplished separately.
结合各向异性扩散和双边滤波的图像去噪
本文提出了一种新的基于非线性扩散和双边滤波相结合的图像去噪技术。该算法利用残差图像的加权局部方差(Weighted Local Variance, WLV)来确定纹理和精细细节。这些区域通过双边滤波去噪,然后返回到用P-M方法去噪的图像。事实上,WLV在这种组合的数量上起着控制作用。对残差图像进行去噪,并将残差图像加入到主去噪图像中是本文的主要创新思想。实验结果表明,该图像去噪方法比非线性扩散和双边滤波分别进行去噪时效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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