| 小波变换结合MIVP识别图像脉冲噪声的研究 |
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| 引用本文： | 匡羽飞,朱嘉钢.小波变换结合MIVP识别图像脉冲噪声的研究[J].计算机工程与应用,2011,47(25):190-193. |
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| 作者姓名： | 匡羽飞 朱嘉钢 |
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| 作者单位： | 江南大学信息工程学院,江苏无锡,214122 |
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| 摘 要： | 提高脉冲噪声的识别率是提高去除脉冲噪声效果的关键。利用小波变换检测信号奇异点的原理,小波变换可用于识别信号中的脉冲噪声。实验表明,在小波变换识别数字图像的脉冲噪声时,由于将受到脉冲噪声污染的像素点判别为未受脉冲噪声污染的像素点的误判率较高,影响了小波变换识别脉冲噪声的整体精度。为了有效解决这一问题,提出了一种基于统计理论的数字图像脉冲噪声统计量识别法称之为MIVP法,可以弥补小波变换误判噪声点为非噪声点的不足。以小波变换结合MIVP法为基础构成图像脉冲噪声滤波器,在不增加时间复杂度的条件下,有效提高了脉冲噪声的滤波效果。
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| 关 键 词： | 图像恢复 脉冲噪声 小波变换 大数定律 中心极限定理 |
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Research of image impulse noise recognition based on wavelet-transform combined with MIVP method |
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| KUANG Yufei,ZHU Jiagang.Research of image impulse noise recognition based on wavelet-transform combined with MIVP method[J].Computer Engineering and Applications,2011,47(25):190-193. |
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| Authors: | KUANG Yufei ZHU Jiagang |
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| Affiliation: | KUANG Yufei,ZHU Jiagang College of Information Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China |
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| Abstract: | The rightness of recognizing impulse noise is the key to the effectiveness of denoising.Wavelet transform can detect impulse noise in signals based on the principle that it can detect signal's singular point.Experimental study shows that the total noise identification accuracy is affected by the error rate that a pixel polluted by impulse noise may be identified as a normal pixel when wavelet transform is used to identify impulse noise.In order to effectively address this issue,a statistical theory based me... |
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| Keywords: | image restoration impulse noise Wavelet Transform(WT) law of large numbers central limit theorem |
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