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基于小波变换的信号奇异性检测，小波模极大值的计算(The signal singularity detection based on wavelet transform )

说明：  Gabor滤波器，可以对图像进行二维Gabor小波变换，用来特制提取(Gabor filter can be two-dimensional Gabor wavelet transform image, for a special extraction)

基于小波变换方法的去雾源代码图像复原代码(Wavelet-based approach to image restoration fog source code)

说明：  短时傅里叶变换的MATLAB实现代码，有效完成时频分析(matlab implementation code of short-time Fourier transform to effectively complete time-frequency analysis)

主要讲述小波变换在信号分析和图像处理中的应用，英文版。(Wavelets applications in signal and image processing)

本文通过比较第一代和第二代小波算法特点,引入二代小波提升结构的概念,提出了一种基于二代小波提升结构的快速图像边缘检测算法 对三次B样条小波基实现提升格式,通过计算大尺度下分解子图的模值和幅角来确定边缘 经过实验比较,能比经典的边缘检测算法得出更精确的边缘图像,同时通过与基于第一代小波算法的边缘检测比较,基于二代小波提升格式的边缘检测算法计算更快速,更高效。(In this paper, by comparing first-and second-generation wavelet algorithm features, the introduction of second generation wavelet to enhance the concept of structure, a second generation wavelet-based structure to enhance the rapid image edge detection algorithm on the three B-spline wavelet lifting scheme to achieve through Calculation of large-scale mold subgraph decomposition value and increase the edge angle to determine the experimental comparison, than the classical edge detection algorithm to draw a more accurate edge image, at the same time with the first generation of wavelet-based edge detection algorithm comparison, based on the Second generation wavelet lifting scheme edge detection algorithm is faster and more efficient.)

相关性小波去噪的程序实现，相关性去噪的程序实现(Wavelet denoising procedures related implementation procedures related to implementation of denoising)

对输入的二维灰值图像，先进行提升Haar小波变换，再用经典的EZW算法对小波系数进行压缩，然后反变换重构原图像。(On the importation of two-dimensional gray value of images, first upgrade the Haar wavelet transform, and then classical EZW algorithm to compress the wavelet coefficients, and then inverse transform reconstruction of the original image.)

Fast Wavelet Transform

此示意程序用DWT实现二维小波变换 1.调原始图像矩阵 2.进行二维小波分解 3.分解结果显示 重构源图像及结果显示 (This indicated the procedure using two-dimensional wavelet transform DWT realize one. Transferred the original image matrix 2. To carry out two-dimensional wavelet decomposition 3. Decomposition results show that reconstruction of the source images and results show)