wavelet

基于小波变换的图像拼接。 本程序利用小波变换的原理实现图像的上下，左右以及斜方向的无缝拼接(Wavelet-based image stitching. The procedure to achieve the principle of wavelet transform image from top to bottom, left and right oblique direction and seamless)

用于折射波处理时的to、θ函数法求界面深度，浅层地震(Used for refraction wave in processing, θ function method to ask interface depth, shallow earthquake)

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)

说明：  小波变换是一种新的变换分析方法，一个迅速发展的新领域(Wavelet transform is a new transform analysis method and a rapidly developing new field)

本人自己编写的小波变换脊提取程序，可用与信号分析．欢迎指导．(I have written wavelet transform ridge extraction procedures, can be used with the signal analysis. Welcomed the guidance.)

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)

shearlet图像融合的源代码，速度很快，做毕业设计的可以参考(shearlet fusion source code, very fast, do graduate design can refer to)

说明：  提出了一种结合SVD的小波变换方法，对其在外弹道测量数据中的野值剔除进行了研究。对观测数据进行小波分解，将小波分解后的近似分量和细节分量组合实现相空间重构，作为SVD方法的输入观测矩阵，根据奇异 熵增量准则，对奇异值进行筛选，根据SVD逆变换重构原信号。这一方法克服了Hankel矩阵相空间构建方法数据 端点失真问题。以小波分解后分量重构的相空间可以满足正交性，进一步提高了SVD进行数据降噪和野值检测的精度。仿真数据和试验数据处理结果证明了这一方法的有效性。(Proposed a method of combining the SVD wavelet transform its outer ballistic measurement data in excluding outliers were studied. Observational data on wavelet decomposition, wavelet decomposition of the approximate combined component and detail component to achieve the phase space reconstruction, as the input observation matrix SVD method, based on singular entropy increment standards, singular value filter, according to the inverse transform heavy SVD structure of the original signal. This approach overcomes the Hankel matrix phase space construction method data endpoint distortion. Wavelet decomposition component of reconstruction phase space satisfy orthogonality, to further improve the SVD for data noise reduction and outlier detection accuracy. Simulation data and experimental data processing results prove the effectiveness of this approach.)

基于小波变换的通信信号码元速率估计.pdf(Estimated rate based on the communication signal element wavelet transform. Pdf)

使用小波变换进行图像去噪，对得到的高频部分利用软阈值和硬阈值法去噪(Image denoising using wavelet transform, the high frequency part by the use of soft threshold and hard threshold denoising)