CS_LBP

改进的harris角点检测代码，应用于基于特征的遥感影像配准中，在经典harris算子基础的改进，提高角点检测的准确度(improvement of harris corner detection program，applied in RS imagery registration based on features，the operator improved on the base of the classical one，the accruacy has been enhanced )

spiht 图形程序压缩代码 代码可用 请仔细研读 并适当修改为适合自己的 (SPIHT graphics program to compress code code available, please carefully read and amended as appropriate for their own)

用MATLAB实现不规则图像的面积测量，采用像素灰度值的占比进行实现(Area Measurement of Irregular Images Using MATLAB)

画图源程序-图像数据显示，可以对数据进行时间轴的曲线显示，也可以是空间轴的多维显示 (Paint source- the image data, the data can be curve shows the time axis, it can be multi-dimensional display space axis)

说明：  图像采集，简单的c#联合halcon做ncc模板匹配的操作(Image acquisition, simple C# combined with Halcon to do NCC template matching operation)

此算法用于对图片进行光照补偿，并对补偿前后的图片进行对比。(This algorithm is used for illumination compensation, and compensation before and after pictures comparing picture.)

本程序使用dcmtk库，可以显示大部分的DICOM图像。非压缩、压缩黑白图像以766灰阶显示，彩色图像正常显示。 对于初用dcmtk库的开发者来说，入门较难，本程序已使用VC6工程将主要库加入工程中，可以参考本工程的设置。另外，对于高于8位的黑白图像，本程序也提供一个处理方法的参考。(This procedure used dcmtk library, you can see that the majority of the DICOM image. Non-compressed, compressed to 766 gray-scale black-and-white images show that color image display. Dcmtk library used for the early developers, the entry more difficult, the procedure has been in use for the main library VC6 project will join the project, can refer to the project settings. In addition, higher than the 8-bit black-and-white images, the program also provides a reference method.)

游程编码是是一种有效的信源编码，能够实现对二值化的图像或者二元序列进行压缩，且具有较好的压缩率。(this program is a good kind of RLC. It could come out rlc, and could compression binary sequences and image )

说明：  用于立体匹配的三种算法，显示视差图，matlab代码(Three algorithms for stereo matching, display parallax map, matlab code)

该代码用于实现视觉目标跟踪研究中的协方差跟踪，能够把多种时空特征融合于统一的模型中，在实现视觉目标跟踪时具有较好的鲁棒性，而且其维数等于使用特征的数量，与各个特征的维数无关，因此，其计算复杂度较小，实时性较好。(This code is used to realize covariance tracking in the research field of visual object tracking of computer vision. It enables fusion of various spatial-temporal features into an unified object feature model, hence robust to noise. In addition, its dimension is equal to the number of the features used and independent of the dimensions of the features used. Therefore, it satisfies the requirement of real-time application due to its low computation cost.)