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遥感图像时空融合，朱孝林博士的作品，可以参考学习(Space-time Fusion of Remote Sensing Images, Zhu Xiaolin)

说明：  使用matlab平台进行斜视角为0度的九点目标RD算法仿真(Simulation of nine point target Rd algorithm with 0 degree squint angle using MATLAB platform)

基于小波阈值的去噪方法，可以通过改变不同的参数达到不同的效果。(Wavelet threshold de-noising method can achieve different effects by changing the different parameters.)

matlab下图像处理技术在智能交通中的应用 主要是小车的跟踪和标示(matlab image processing technology under the Intelligent Transportation System in the main car tracking and labeling)

实现数字图像处理的直方图均衡化，将一幅灰度图像的频谱展示处理(histogram equalization)

A Drawable that manages an array of other Drawables. These are drawn in array order, so the element with the largest index will be drawn on top.

这是基于图论的图像分割源代码，效果很好，欢迎下载.(This is based on graph theory image segmentation source code, works well, welcome to download.)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

说明：  用MATLAB进行图形样板匹配的源程序，（开发平台MATLAB7.0）(Using MATLAB graphics to match the source model, (development platform MATLAB7.0))

基于象素的图像配准程序,要配准的两幅图像,通过多对对控制点来配对(Pixel-based image registration procedures are based on the registration of two images, through a multi-right right control point to the matching)