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基于相似度的图像质量评价算法Structural SIMilarity (SSIM) index的实现。(This is an implementation of the algorithm for calculating the Structural SIMilarity (SSIM) index between two images. Please refer to the following paper: Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity" IEEE Transactios on Image Processing, vol. 13, no. 4, pp.600-612, )

几个大牛对集成了国内外特征提取最前沿的算法，特征提取，DOG,HARRIS,HARRIS-LAPLACE,HARRIS-AFFINE,MSER.描述符，SIFT,AFFINE-SIFT,GLOH.经测试，速度快，描述符准确。(Integration of feature extraction algorithms from several expert of domestic and international, feature extraction： DOG, HARRIS, HARRIS-LAPLACE, HARRIS-AFFINE, MSER； Descriptors： SIFT, AFFINE-SIFT, GLOH. The test reveal the speed and accurate descriptor.)

彩色图像分割算法，首先基于直方图粗分，而后通过kmeans细分，得到分割结果(Color image segmentation algorithm, first, rough segmentation based on histogram and then broken down by kmeans get segmentation results)

包含canny edge detector 和 shape context 的优化计算。(Contains the canny edge detector and the shape context of the optimization calculation.)

一个运动估计运算的MATLAB文件，本人已经测试过，非常有用。(A motion estimation MATLAB file operations, I have been tested, very useful.)

基于ART算法的CT图像重建 刚找到的，不知能不能用(CT image reconstruction based on ART algorithm)

matlab OTSU 简易的大津算法 求最佳阈值的。(matlab simple algorithm seeking Otsu threshold.)

tiff图像的读取与处理，并且说明清新，有很大的帮助。(The reading and processing of the tiff image, and the description of the fresh, is of great help.)

针对可见光与红外图像的特点和难点，提出了可见光与红外图像配准与融合中的关键技术，即: 使用新型的基于一维最大类间方差和最大连通性测量的图像分割方法对源图像进行分割来更好地实行图像粗 配准 使用新型的特征点提取方法，特征点的匹配及误匹配的消除来更好地实行图像精配准 采用新型的基 于区域的树状小波活性测度计算来实现树状小波图像融合 利用自生成神经网络来实现模栩图像融合. (For visible light and infrared images of the characteristics and difficulties, a visual and infrared image registration and integration of key technologies, namely: the use of new one-dimensional based on the largest variance between-class connectivity and the largest measuring method of image segmentation source image segmentation to better implementation of coarse image registration the use of a new type of feature point extraction method, feature points of the match and the elimination of false matches to better the implementation of image fine registration the use of new tree-based wavelet calculated to measure the achievement of the activity tree wavelet image fusion the use of self-generating neural network to achieve image fusion Xu mode.)

对矩形件的排样过程进行编码实现，通过visual c++(layout problem)