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对于传统去噪模型的大幅改进，之前的模型都会出现阶梯效应的现象，采取了新的模型对图像进行建模，有效改善了图像去噪图像修复等过程中引入的阶梯效应，而且一定程度上对于图像纹理的修复也有很大的作用(For significantly improve the traditional de-noising model, the model will appear before the phenomenon of the staircase effect, to take a new model for image modeling, effectively improved the staircase effect denoising image restoration process introduced, and to a certain extent for texture of repair also has a significant role)

一种改进后的海森矩阵算法代码，针对医学图像处理效果比较好，可以识别较细的血管。(An improved Hessian matrix algorithm code, medical image processing effects for better, you can identify smaller vessels.)

image processing for hand guesture

VC++处理图像模糊或柔化的效果示例源程序，类似Photoshop中的图像高斯模糊效果，每点击一次鼠标右键，程序为模糊一次，直到你满意为止。注意程序仅实现了模糊的功能，其它功能比如程序优化和效率方面的考虑还比较少，因此程序运行速度方面可能会欠缺一些(VC++ deal with image blur or soften the effect of sample source code, similar to Photoshop' s image Gaussian Blur effect, each click the right mouse button, the procedures for fuzzy time until you are satisfied. Note that the program is only vague functions, other functions such as process optimization and efficiency considerations is still relatively small, the speed of the program is running may lack some of the)

说明：  一个用VC++6.0编的程序例子，实现远程屏幕图像的传输 (a VC 6.0 Provision procedures example, remote screen image transmission)

一种快速图像阈值分割法，不是otsu或迭代法，Wellner 1993快速自适应的图像二值化方法，有具体使用方法，很详细(A fast image thresholding segmentation method, not otsu or iterative methods, Wellner 1993 fast adaptive image binarization method)

利用Matlab的图形用户界面（GUI）编程实现1.信号产生,信号基本运算,傅立叶变换 2.图像文件的读取和显示,图像增强,边缘检测,图像的数学变换(Using Matlab' s graphical user interface (GUI) programming 1. Signal generation, signal basic operations, Fourier transform 2. Read and display image files, image enhancement, edge detection, image of the mathematical transformation)

图像处理，手写数字识别，GUI界面内自写数字，可以用来学习。(Image processing, digital handwriting recognition, digital write within the GUI interface, can be used to learn.)

基于加权最小二乘的滤波器。实现应用的例子。(weighted least square)

说明：  基于DWT域的脆弱水印，上数字图像处理课的大作业(Fragile watermarking based on DWT, digital image processing course)