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Spatially varying weighted HSI diffusion for color image denoising

机译:用于彩色图像去噪的空间不同加权HSI扩散

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This paper presents a novel anisotropic diffusion framework for color image denoising. Unlike previous approaches, our method is based on separating a color image into hue, saturation and intensity (HSI) components, and then diffusing each component with spatially varying weighted partial differential equations (PDE). The hue denoising is implemented by a new weighted orientation diffusion, and the saturation diffusion is a modified curvature flow. The intensity diffusion PDE is a combination of a gradient vector flow (GVF)-based filter and a fourth-order filter. This combined technique provides a robust and accurate denoising process, i.e., it preserves edges well and at the same time overcomes the staircase effect in smooth regions. The denoising experiments on a set of standard color images have shown satisfactory results.
机译:本文提出了一种用于彩色图像去噪的新的各向异性扩散框架。与先前的方法不同,我们的方法基于将彩色图像分离为色调,饱和度和强度(HSI)分量,然后将每个组件扩散为空间变化的加权部分微分方程(PDE)。色调去噪由新的加权取向扩散实现,饱和扩散是修改的曲率流动。强度扩散PDE是基于梯度向量流(GVF)的滤波器和四阶滤波器的组合。这种组合技术提供了一种坚固且准确的去噪过程,即,它保持良好的边缘,同时克服平滑区域中的楼梯效果。一组标准彩色图像上的去噪实验表明了令人满意的结果。

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