在MATLAB环境下，P0309运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理...

可用于256色位图文件的轮廓跟踪，以及对图像边缘提取。-256 colors can be used to outline bitmap file tracking, as well as the image edge extraction.

依据论文：《灰度图像增强算法的改进与实现研究.caj》中的算法，实现灰度图像的增强处理，经试验表明，效果不错。-Based on papers:

仿射变换法求深度信息，目前最好的方法 function [Z,D11,D12,D22] = diffusion_kernel_function(gx,gy,im) gx,gy 为x,y方向偏导数 Z 为恢复出来的是深度信息。 函数适应于从 图像法相信息恢复高度信息-Affine transformation method the depth of information, is currently the best way to function [Z, D11, D12, D22] = diffusion_kernel_function (gx, gy, im) gx, gy for x, y direction of the partial derivative of Z is out to restore the depth of information. Function adapted from the image information to resume a high degree of information law

散乱数据类型，对三维重构中数据的预处理，对于三角网格化提出了一种相邻轮廓同步前进法，达到了很好的效果。-Scattered data type, three-dimensional reconstruction of the data pre-processing, for the triangular grid paper, a simultaneous advance adjacent contour method achieved very good results.

转用于3G手机应用开发的android代码，示例是如何使用广播-Turn the development of applications for 3G mobile phones android code example is how to use the radio

利用GAC水平集迎风方案实现图像分割，分割效果较好，收敛速度快-GAC sets the level of use of the wind program to achieve image segmentation, segmentation better, faster convergence

sift的c++算法，不是基于opencv的，我自己没有看懂。-sift the c++ algorithm, is not based on the opencv, as I do not understand.

2005/12/07 此程序主要使用mallet算法实现的是97小波变换程序 -2005/12/07 The procedure used mallet algorithm is 97 Wavelet Transform Procedure

svm matlab toolbox（SVM的MATLAB工具箱）-svm matlab toolbox (SVM in MATLAB toolbox)

本文提出了一种新的跨国家的障碍 检测技术为基础的立体视觉系统。 原始图像的预处理的高斯 过滤器和对比度限制的自适应直方图 均衡（ CLAHE ）方法来削弱作用 噪音，光线和对比度。哈里斯的角落位于与子像素精确。 -Cross-country intelligent vehicles always work in complicated environments with varying illuminations. The paper presents a new cross-country obstacle detection technology based on stereo vision system. The original images are preprocessed by Gaussian filter and contrast-limited adaptive histogram equalization (CLAHE) method to weaken the effect of noise, light and contrast. Harris corners are located with sub-pixel accurate. To guarantee the overall system real-time performance, feature-based matching techniques are studied and fundamental matrix is calculated based on random sample consensus (RANSAC). Also restrains are studied to eliminate pseudo matching pairs. Then data interpolation is introduced to build elevation maps. Edge extraction and morphological processing are concerned to accomplish obstacle detection. Experiment result