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在matlab中实现透视变换。算法正确高效，这种仿射变换经过修改后可用于图像矫正或者摄像机标定等用途。(Matlab in perspective transformation. Correct and efficient algorithm modified this affine transformation can be used to image correction or camera calibration purposes.)

这里的图像增强包括灰度修正、平滑、滤波、锐化等，是图像处理的基本操作，本代码调试通过(Here, including gray-level correction image enhancement, smoothing, filtering, sharpening, etc., is the basic image processing operations, the code debugging by)

k均值算法的matlab程序，可直接运行。(k-means algorithm matlab procedures, can be directly run.)

基于MATLAB实现图像融合，左右焦距融合(Image fusion based on MATLAB,Left and right focal length fusion)

识别结果详见下图，识别图像不错的例子

基于双目的深度图获取,根据图像合成深度图左右视点( depth map based on binocular)

说明：  MATLAB如何将图片切分成任意M*N块 在图像处理的时候，有时会不可避免的将图像分块来进行操作，但是图像的像素不可能每次都是可以被整除的，所以我们需要imresize函数对图像的尺寸进行修改，以便可以完成M*N块的分割(How can matlab cut the image into any m * n blocks? Sometimes it is inevitable to divide the image into blocks for operation. However, the pixels of the image can not be divided every time. So we need to modify the size of the image with the function of reduce to complete the m * n block segmentation)

图像分割，显著性算法的precision，recall 和ROC的评价指标计算。(Image Segmentation, significant precision,recall and ROC assessment index calculation algorithm.)

针对分水岭算法存在的过分割问题以及VCH-F1切片图像的特点，提出一种能够有效消除局部极小值和噪声干扰的自动分割方法。首先比较彩色分量梯度图，选择分量图像的梯度信息，达到有效提取图像边缘信息的目的；然后提出基于多阈值分割的方法消除无效梯度信息；最后介绍了算法的步骤及结果。实验结果证明，通过该方法处理的梯度图像再进行分水岭算法处理，即使不进行区域合并也能达到很好的效果。(Watershed algorithm for over-segmentation problem of the existence of VCH-F1 as well as the characteristics of the image slice, a can effectively eliminate the local minimum value and noise automatic segmentation method. Comparing the first color component gradient map, select the quantity of image gradient information, achieve an effective extraction of image edge information purposes then made based on multi-threshold segmentation method to eliminate invalid gradient information Finally introduce the steps of the algorithm and results. Experimental results show that the adoption of the method of treatment of gradient watershed algorithm for image re-treatment, even if there is no regional merger will also achieve good results.)

智能图像处理提出了一种改进的基于特征和回归分析的人群密度估计算法。引入图像中的角点个数作为低层特征(Interactive Images: Cuboid Proxies for Smart Image Manipulation)