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Impulse noise removal using SVM classification based fuzzy filter from gray scale images

机译：使用基于SVM分类的模糊滤波器从灰度图像中去除脉冲噪声

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摘要

In this paper, support vector machine (SVM) classification based Fuzzy filter (FT) is proposed for removal of impulse noise from gray scale images. When an image is affected by impulse noise, the quality of the image is distorted since the homogeneity among the pixels is broken. SVM is incorporated for detection of impulse noise from images. Here, a system is trained with an optimal feature set When an image under test is processed through the trained system, all the pixels under test image will be classified into two classes: noisy and non-noisy. Fuzzy filtering will be performed according to the decision achieved during the testing phase. It provides about 98.5% true-recognition at the time of classification of noisy and non-noisy pixels when image is corrupted by 90% of impulse noise. It leads to improvement of Peak-signal to noise ratio to 22.2437 dB for the proposed system when an image is corrupted by 90% of impulse noise. The simulation results also suggest that how this system outperforms some of the state of art methods while preserving structural similarity to a large extent.
机译：本文提出了一种基于支持向量机（SVM）分类的模糊滤波器（FT），用于去除灰度图像中的脉冲噪声。当图像受到脉冲噪声的影响时，由于像素之间的均匀性被破坏，因此图像的质量失真。支持SVM，用于检测图像的脉冲噪声。在这里，使用最佳功能集训练系统当通过训练后的系统处理被测图像时，被测图像的所有像素将被分为两类：有噪和无噪。模糊过滤将根据在测试阶段获得的决定进行。当图像被90％的脉冲噪声破坏时，在对有噪声和无噪声像素进行分类时，它可以提供约98.5％的真实识别。当图像被脉冲噪声的90％破坏时，对于所提出的系统，它可以将峰值信噪比提高到22.2437 dB。仿真结果还表明，该系统如何在保持结构相似性的同时胜过某些现有方法。

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  • 来源
    《Signal processing》 |2016年第11期|262-273|共12页
  • 作者

    Amarjit Roy; Joyeeta Singha; Salam Shuleenda Devi; Rabul Hussain Laskar;

  • 作者单位

    Speech and Image Processing Group, Electronics and Communication Engineering Department, National Institute of Technology, Silchar, Assam 788010, India;

    Speech and Image Processing Group, Electronics and Communication Engineering Department, National Institute of Technology, Silchar, Assam 788010, India;

    Speech and Image Processing Group, Electronics and Communication Engineering Department, National Institute of Technology, Silchar, Assam 788010, India;

    Speech and Image Processing Group, Electronics and Communication Engineering Department, National Institute of Technology, Silchar, Assam 788010, India;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Impulse noise; Support vector machine; Artificial neural network; Fuzzy filter;

    机译：脉冲噪声;支持向量机;人工神经网络;模糊滤波器;

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