Source

说明：  基于vc++6.0 的图像对比度拉伸操作(vc 6.0 on the image contrast stretching operation)

实现离散余弦(TCD)变换(achieve discrete cosine (TCD) Transform)

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)

基于小波变换的图片重建 有完整代码 工程 以及说明 涉及到图片的切割(image reconstruction based on wavelet translate )

说明：  小波变化代码，是比较好的测试向量，包括位平面编码和MQ(Wavelet transform code, is a better test vectors, including the bit plane coding and MQ)

通过设计Visual C程序源码对简单易懂的一维信号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波与Haar小波变换，从而的到小波分解系数；再通过改变分解的到的各层高频系数数进行信号的小波重构达到消噪噪的目的。在这一程序源码实现的过程中能直观地理解信号小波分解重构的过程与在信号消噪中的重要作用，和在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。 可直接 (Design Visual C program source code on a simple one-dimensional signal with a Gaussian white noise Daubechies wavelet, Morlet wavelet and Haar wavelet transform, and thus to the wavelet coefficients and then change the decomposition to each storey wavelet reconstruction frequency coefficient of the number of signal to noise canceling noise. In the process of realization of this program source code can be intuitively understood the signal wavelet decomposition and reconstruction process and an important role in signal denoising, and the selection coefficient in the high frequency coefficients of the layers of the weight of processing noise cancellation signal impact. Can be directly)

Wavelet compression algorithm. Start by computing a complete wavelet-transform using the cohen-daubechies-fevereau (2,2) biorthogonal wavelet (which incidentally seems to be the same as used for lossless JPEG2000, but they call it a (5,3)?).

本文实现基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法，相比较其它的小波去噪算法而言，效果非常好(This realization based on Bayesian (BAYES) Threshold the wavelet (WAVELET) image denoising algorithm, compared with other wavelet denoising algorithm, the effect was very good)

9/7 二维整数小波变换，可以实现图像的无损恢复。(9/7 two-dimensional integer wavelet transform, you can realize non-destructive restoration of images.)

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)