基于HMIS的微藻图像噪声模型与滤波技术的对比研究

K. Pavendan, N. Vinitha, K. P. Gopinath
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引用次数: 0

摘要

在生物建筑中,微藻的存在大多是作为水污染监测的一种手段。最近,创新的进步从根本上增强了检查计算机图像的能力。他的工作提出了从计算机图像中排除不同过滤的分离程序。在任何情况下,这种噪声世界观取决于干扰的种类,可以使用线性和非线性滤波框架来减少干扰。由于图像中存在不同类型的滤波,因此可以利用滤除算法去除噪声。此外,本文还提出了将不同的过滤器分类应用于图片的结果并进行了探讨。因为,图像中噪声减小的原创性是通过实际和度量来衡量的,例如,均方根误差(RMSE)和峰值信噪比(PSNR)。采用维纳隔离框架对不同滤波级别的不同噪声损坏的图像进行了区分处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comparative study on noise models an d filtering techniques using HMIS based microalgae images
In biological building, presence of microalgae are for the most part used as a piece of monitoring of water pollution. Most recently, innovative advancement has fundamentally enhanced in examining computerized pictures. his work proposes the separating procedures for expulsion of different filtering from computerized pictures. In any case, this noises worldview depends on kind of disturbances, which can be diminished using linear and non linear filtering frameworks. Since, different sort of filtering exhibit in a picture, noises can be expelled utilizing filtering expulsion calculation. Additionally, this paper produces consequences of applying diverse filter sorts to a picture and explored. Since, the originality of noise diminishing in pictures is measured by the real sum measures, for instance, Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR). The execution of these filters on pictures corrupted with different noise of various filtering levels is differentiated and Wiener isolating framework.
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