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A Novel Image Denoising Method Based on Force Field Transform

机译:一种基于力场变换的新型图像去噪方法

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摘要

As a fundamental image processing operation, a good denoising method should keep the original image information as much as possible. However, most denoising methods may degrade or remove the fine details and texture of the original image. In this paper, a force field method is adopted to transform the image pixels within a local window into a potential energy surface and then to distinguish the image edges and the noises in this potential energy field. Afterwards, different templates are used according to the judgment and the adaptive filter is applied to the local pixels respectively. This new method has less computational complexity than the other algorithms of transform domain, which means it can be implemented in a real-time processing system. Also the new method can preserve more image edges than the traditional filters. Finally the performance of the proposed method is compared in this paper with other popular methods by using evaluation criterion of SNR and SSIM(a measure of structural similarity). The results show that the proposed method is reliable and especially helpful to preserve the image details.
机译:作为基本图像处理操作,良好的去噪方法应尽可能地保持原始图像信息。然而,大多数去噪方法可能会降低或去除原始图像的精细细节和纹理。在本文中,采用力现场方法将本地窗口内的图像像素转换为潜在能量表面,然后在该潜在能量场中区分图像边缘和噪声。之后,根据判断使用不同的模板,并且分别将自适应滤波器施加到局部像素。这种新方法的计算复杂性较少而不是变换域的其他算法,这意味着它可以在实时处理系统中实现。此外,新方法可以保持比传统过滤器更多的图像边缘。最后,通过使用SNR和SSIM的评估标准(结构相似度的量度),将本文的性能与其他普遍的方法进行了比较了所提出的方法的性能。结果表明,该方法可靠,特别有助于保留图像细节。

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