2013.10.17program-engineer

给定的n个点在二维平面上,发现的最大数量点躺在同一直线。(Given n points on a 2D plane, find the maximum number of points that lie on the same straight line. )

完成流程编码和huffman编码，适合做图像编码的熵编码，只要调整接口就好。(Complete the process encoding and huffman coding, image coding suitable for entropy coding, as long as the adjustment of the interface is like.)

亚像素方面的相关源码!!!相信对你的学习会有帮助!(Related to source sub-pixel area!!! That would be helpful to your learning!)

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)

KRUSAL算法实现最小生成数的 最小生成数的 最小生成数的(The KRUSAL algorithm realizes the minimum generating number of the minimum generating numbe)

直线段检测算法EDLines C++实现(EDLines C++ Opencv lins segment detection)

Image_processing in C

多光谱图像出理，离散傅立叶变换，低通滤波，TM条带影像去除(multispectral image integration of remote sensing)

针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )

很有用的gdal库，并且已经编译好。请多多指教!(It is a very good resource！Please download！！)