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利用极大似然估计进行盲反卷积复原，通过多帧图像约束，效果较好(Use of maximum likelihood estimates for blind deconvolution restoration by the multi-frame image constraint, the better)

cholesky算法信号稀疏解 对于数据压缩有很大帮助(we are the world we are the children we are the ones)

RMSHE算法（recursive mean-separate histogram equalization）。基本原理是将图像根据平均灰度进行分割，各部分分别进行直方图均衡。文件中包含RMSHE的matlab源代码，论文，以及输入图像(RMSHE algorithm (recursive mean-separate histogram equalization). The basic principle is that the image based on the average gray-scale is divided, each part respectively histogram equalization. File contains RMSHE matlab source code, papers, as well as the input image)

着重介绍了数字水印Patchwork 算法，并且利用Matlab编程实现了这一算法(Focuses on digital watermarking Patchwork algorithm, and this algorithm Matlab programming)

说明：  利用小波进行边缘提取，比较各种小波核函数的能力，体会“数学显微镜”的妙用，例子：车牌定位。(using wavelet edge detection, comparison of different wavelet function of the nuclear capability and experience "math microscope," the magic examples : positioning plates.)

图像去模糊处理的matlab源程序，附带源图片。是在经典图像模糊化的基础上进行恢复的，不是盲恢复(Image to fuzzy treatment matlab source, and with the source images. In classic blur image is conducted on the basis of the recovery, not blind recovery )

说明：  将girl 图像进行分割，达到2*4的图像分割结果。并使用tight_subplot函数将分割间距变小。(The girl image is segmented to achieve a 2*4 image segmentation result. And use the tight_subplot function to make the division interval smaller.)

segmentation using region growing in an image

pcnn 彩色图像分割中，是非常有用的一个程序！！！！！！(PCNN is applied to the color image segmentation.it is very very very very useful!)

rgb to HSV，很有用，调试成功，可以应用(rgb to HSV，#include "stdafx.h" #include <iostream.h> void main(float R, float G, float B, float& H, float& S, float&V) { // r,g,b values are from 0 to 1 // h = [0,360], s = [0,1], v = [0,1] // if s == 0, then h =-1 (undefined) float min, max, delta,tmp tmp = R>G?G:R min = tmp>B?B:tmp tmp = R>G?R:G max = tmp>B?tmp:B V = max // v delta = max- min if( max != 0 ) S = delta/max // s else { // r = g = b = 0 // s = 0, v is undefined S = 0 H = 0 return } if (delta == 0){ H = 0 return } else if(R == max){ if (G >= B) H = (G- B)/delta // between yellow & magenta else H = (G- B)/delta+ 6 } else if( G == max ) H = 2+ ( B- R )/delta // between cyan & yellow else if (B == ma)