image-fusion

多点目标 单站SAR的回波信号仿真以及BP后向投影成像 参数见合成孔径雷达成像——算法与实现一书表6.1 运行结果正确，注释比较详细(Percent more single station SAR point target echo signal simulation and backward projection imaging BP parameters, see synthetic aperture radar imaging- algorithm and implementation of a book Table 6.1 run result is correct, more detailed notes)

基于小波变换的心电信号预处理MATLAB源代码(The heart preprocessind based on wavelet transform)

对图像进行小波变换的分解和重构的代码，包含以为信号的处理。( The image decomposition and reconstruction of wavelet transform code, including that the processing of the signal.)

利用小波变换，通过设置阈值对图像进行去噪。 首先对图像用小波进行2层分解，然后通过设置硬阈值和软阈值的方法，对图像高频部分去噪。(The wavelet transform is used to denoise the image by setting threshold. Firstly, the image is decomposed into 2 layers by wavelet, and then the high frequency part of the image is denoised by setting the hard threshold and the soft threshold.)

dual tree complex wavelet transform

以labview为平台通过小波分析方法对波形进行处理。(Labview as a platform for analysis of the waveform by wavelet processing.)

对信号进行小波去噪再重构，针对不同分解层次的高频系数，采用分层阈值方式来量化高频系数。(Signal is carried out the wavelet denoising again reconstructed to quantify high-frequency coefficients, high-frequency coefficients for different levels of decomposition, hierarchical threshold.)

图象增强小波变换将一幅图象分解为大小、位置与方向都不同的分量。在做逆变换之前能改变小波变换域中某些系数的大小，，这样就能够洋选择的放大所感兴趣的分量而减小不需要的分量。给定一个图象信号，用二维小波分析析对图象进行增强处理。 (Image enhancement wavelet transform decomposition size, location and direction of the different components of an image. Wavelet transform domain, some the size of the coefficient can change before doing the inverse transformation, so can the component of interest to the amplification of the ocean choose to reduce the unwanted weight. Given an image signal, the analysis of two-dimensional wavelet analysis of image enhancement processing.)

EEG采集脑电波，然后用小波变换分析睁眼时产生脑电波的频率及各项数据(EEG brain waves collected and then analyzed using wavelet transform eyes when the frequency of brain waves generated and the data)

D5/3提升整数小波，可实现图像的无损压缩，包括一维和二维图像整数小波变换(D5/3 integer wavelet upgrade can realize lossless image compression, including the one-dimensional and two-dimensional image integer wavelet transform)