labview-wavelet-analysis-help-file

用MATLAB编写的利用小波变换对多聚焦图像的融合。(The fusion of multi focus images with wavelet transform is written in MATLAB.)

多尺度图像非下采样轮廓波变换（NSCT）的工具箱，实现代码为Matlab版本。可用于图像的多尺度分析，如图像压缩、图像分割、图像融合和超分辨率等。(Multi-scale image nonsubsampled contourlet transform (NSCT) toolbox, code Matlab version. The images can be used for multi-scale analysis, such as image compression, image segmentation, image fusion and super-resolution.)

关于最小二乘法的相位解包裹,对于学些图像处理的同学还是很有用的哦~(It s about the least squares method of phase unwrapping )

基于四阶累积量的矩阵方程法子波估计,对研究子波的有一定的帮助(based on the forth cumulantion seismic wavelet estimation)

Wavelet Neural networks

说明：  小波变换技术与工程实践：图像的小波变换(MFC框架下)(Wavelet transform technology and engineering practice: Image Wavelet Transform (MFC framework))

时频分析代码，希望对大家有用，关于盲源分离的基础知识(Time frequency analysis code, we hope to be useful to everyone, about the basic knowledge of blind source separation.)

分别用小波、分形的方法对图像进行去噪，并对这两种方法的结果进行了比较。(Wavelet, respectively, the method of fractal image denoising, and the results of these two methods are compared.)

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.)

说明：  基本的S变换matlab实现 用于时频分析 为初学者提供基本代码(S transformation for time-frequency analysis to provide basic code for beginners)