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Moving window-based double haar wavelet transform for image processing

机译:基于移动窗口的双哈尔小波变换的图像处理

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摘要

Image denoising is a lively research field. The classical nonlinear filters used for image denoising, such as median filter, are based on a local analysis of the pixels within a moving window. Recently, the research of image denoising has been focused on the wavelet domain. Compared to the classical nonlinear filters, it is based on a global multiscale analysis of images. Apparently, the wavelet transform can be embedded in a moving window. Thus, a moving window-based local multiscale analysis is obtained. In this paper, based on the Haar wavelet, a class of nonorthogonal multichannel filter bank with its corresponding wavelet shrinkage called Lee shrinkage is derived. As a special case of this filter bank, the double Haar wavelet transform is introduced. Examples show that it is suitable for a moving window-based local multiscale analysis used for image denoising, edge detection, and edge enhancement.
机译:图像降噪是一个活跃的研究领域。用于图像去噪的经典非线性滤波器(例如中值滤波器)基于对移动窗口内像素的局部分析。近来,图像去噪的研究已经集中在小波域上。与传统的非线性滤波器相比,它基于图像的全局多尺度分析。显然,小波变换可以嵌入到移动窗口中。因此,获得了基于移动窗口的局部多尺度分析。本文基于Haar小波,推导了一类具有相应小波收缩率的非正交多通道滤波器组,称为Lee收缩率。作为该滤波器组的特例,引入了双重Haar小波变换。示例显示,它适用于基于移动窗口的局部多尺度分析,该分析用于图像去噪,边缘检测和边缘增强。

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