Wang Xin
School of Information Science and Engineering, Shandong University, Jinan 250061, China.
IEEE Trans Image Process. 2006 Sep;15(9):2771-9. doi: 10.1109/tip.2006.877316.
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 multi-channel 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.
图像去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，如中值滤波器，是基于对移动窗口内像素的局部分析。近年来，图像去噪的研究集中在小波域。与经典非线性滤波器相比，它基于对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，得到了基于移动窗口的局部多尺度分析。本文基于哈尔小波，推导了一类非正交多通道滤波器组及其相应的小波收缩方法——李收缩。作为该滤波器组的一个特例，引入了双哈尔小波变换。实例表明，它适用于基于移动窗口的局部多尺度分析，可用于图像去噪、边缘检测和边缘增强。
