Noise Removal from Images Using Adaptive Neuro/Network-Fuzzy Interface Systems

Krishna Prasad Pulipaka, K. S. Kumar, K. G. Apoorva, Rohith Rao, K. R. Krishna
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Abstract

Any Information signal is best desirable without any external noise/ disturbances. Noise in any signal is the undesirable quantity present which deteriorates the signal's quality, thus compromising the information. Any signal, be it an image signal (2-D) or else a video signal (3-D) in the field of communication, if not always but most number of times prone to noise. In this paper, we would be dealing with removing types of noise on an image, using various filter techniques such as vector median filter, vector directional filter. Using the image processing tools in MATLAB, we could achieve this quite effortlessly. Looking at the prior approaches and keeping those factors in understanding, this paper would intend to path a more thoughtful way to bifurcate the image from its noise using the techniques of the neural networks. With thorough scrutiny and understanding of filters, this paper ensemble the performance of filters, through which we would be applying the most suitable filter out of the lot with the neural networks.
使用自适应神经/网络模糊接口系统去除图像噪声
任何信息信号最好没有任何外部噪声/干扰。任何信号中的噪声都是不希望出现的量,它会使信号的质量恶化,从而损害信息。任何信号,无论是图像信号(2-D)还是视频信号(3-D),在通信领域,即使不是总是,但大多数时候都容易受到噪声的影响。在本文中,我们将处理去除图像上的噪声类型,使用各种滤波技术,如矢量中值滤波器,矢量方向滤波器。使用MATLAB中的图像处理工具,我们可以毫不费力地实现这一点。考虑到之前的方法,并保持对这些因素的理解,本文打算采用一种更深思熟虑的方法,利用神经网络技术将图像从噪声中分离出来。通过对滤波器的深入研究和理解,本文将滤波器的性能集成在一起,通过神经网络,我们将从众多滤波器中选择最合适的滤波器。
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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