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)

余弦变换-DCT。好用的小波变换方法程序。(Cosine transform-DCT. Use of wavelet transform.)

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.)

小波阈值去噪 软阈值去噪和硬阈值去噪的比较(Wavelet thresholding soft thresholding and hard thresholding comparison)

很好的继续教育教材，提升素质必备啊！不可错过！十分的好(Good continuing education materials, enhance the quality of essential ah!)

dual tree complex wavelet transform

对信号进行局部均值分解，得到一系列具有物理意义的pf分量(Local mean decomposition of the signal to obtain a series of having a physical meaning PF component)

说明：  论文主要包括基于小波变换语音增强的各种算法的介绍。(Articles include speech enhancement based on wavelet transform introduces a variety of algorithms.)

说明：  曲波变换和去噪，可以进行曲波变换阈值去噪，是很好的去噪入门代码。(Curvelet transform and denoising, can be threshold denoising curvelet transform, is a good denoising entry code.)

一种基于DWT小波变换的数字音频水印嵌入方法，供大家参考学习(Based on the the DWT wavelet transform digital audio watermark embedding method for your reference learning)