Image De-noising with Hexagonal Structures Using Adaptive Recursive Filter

M. D. Jakhete, A. Vyas, N. Shinde, Payal Kadam
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Abstract

Single-pass de-noising of images is often inefficient because the de-noised images always contain some or the other part of noise remnants from the single-pass operation. Thus, for true de-noising of the images, we need to re-apply the de-noising algorithm on the image, so that removes a remnant noise from the image and obtained the de-noised image. In this paper, we tend to propose a unique algorithmic rule that uses adaptive recursive algorithmic filtering using hexagonal structure to de-noise images that are debased by salt also pepper commotion. The proposed calculation is contrasted, and a traditional channel calculation based on a square structure. The results show that the planned formula improves the peak Signal to Noise ratio (PSNR) by quite 10 dB regarding typical filter using a structure of square.
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基于自适应递归滤波器的六边形结构图像去噪
由于去噪后的图像中总是含有单遍去噪后的残余噪声,因此单遍去噪往往是低效的。因此,为了对图像进行真正的去噪,我们需要对图像重新应用去噪算法,从而去除图像中的残余噪声,得到去噪后的图像。在本文中,我们倾向于提出一种独特的算法规则,即使用六边形结构的自适应递归算法滤波来去除被盐和胡椒骚乱贬低的图像。并与基于方形结构的传统信道计算方法进行了对比。结果表明,对于使用方形结构的典型滤波器,所规划的公式将峰值信噪比(PSNR)提高了10 dB以上。
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