基于Deslauriers-Dubuc(4,2)小波的提升方案图像去噪方法
详细信息 本馆镜像全文    |  推荐本文 | | 获取馆网全文
摘要
提升小波具有结构简单、运算量低、原位运算、节省缓存空间,逆变换通过结构翻转得到等诸多易于实现的特点。将基于Deslauriers-Dubuc(4,2)小波的提升方案应用于图像的去躁处理中,能快速有效去除信号中的高斯白噪声等。将提升方案与中值滤波相结合,可同时滤除图像中的高斯白噪声和脉冲噪声等。
Wavelet based on lifting has many features easily achieved,for example, simple structure,light calculation task,in-place operation,little temporary memory space,easily reverse transform.This paper(introduces) Deslauriers-Dubuc(4,2) wavelet transform based on lifting scheme,and gets a good result in(image) de-noising to wipe the Gaussian white noise off by using this algorithm.Then it discusses median filter with Deslauriers-Dubuc(4,2) wavelet transform based on lifting,at the same time to filter out the Gaussian white noise and impulse noise.
引文
[1]王建中.基于Daubechies小波和中值滤波的图像去噪法[J].武汉理工大学学报,2001,3(3):19-21.
    [2]Claypoole Roger L,Davis Geoffrev M,Wim Sweldens.Nonlinearwavelet transforms for image coding via lifting[J].IEEE Transactionson Image Processing(Submitted),1999,8:3-6.
    [3]王志武.基于Bernstein滤波器自适应提升小波变换[J].信号处理,2002,6(3):233-236.
    [4]陈香朋.第二代小波变换及其在地震信号去躁中的应用[J].石油物探,2004,11(6):547-550.
    [5]赵爱华.基于提升的自适应图像消噪[J].计算机工程,2003,10(18):151-153.

版权所有:© 2023 中国地质图书馆 中国地质调查局地学文献中心