图像边缘检测

这是bregman迭代的小例子，看完之后对图像处理的优化帮助很大，你可以掌握其中的优化算法，很好，很实用(This is the iterative Bregman small example, after reading on the optimization of image processing helps a lot, you can grasp optimization algorithm, which is very good, very practical.)

CVPR2007，论文“Saliency detection: A spectral residual approach”的源码(a code for "Saliency detection: A spectral residual approach,"CVPR,2007.)

说明：  PCL+ MFC+ Visualization 点云显示(PCL+ MFC+ Visualization)

CODING FOR NEW SEGMENTATION TECHNIQUE

图像拼接,可用于全景照机等应用场景 根据图像的特征（可选多种特征，例如SIFT,haar,HOG等征），将两幅或多幅图像无缝拼接起来(Image stitching, can be applied to panoramic photographing, and other application scenarios.)

Latent SVM算法实现行人检测opencv(Latent SVM Pedestrian Detection Based on Algorithms opencv)

亚像素边缘检测的matlab代码，比一般的边缘检测代码精确(Sub-pixel edge detection matlab code)

说明：  图像融合常见功能，3类共12种图像融合算法，GUI界面，源图像(Common functions of image fusion, 3 types of 12 image fusion algorithms, GUI interface, source image)

说明：  获取图像的LBP特征：对图像的原始LBP模式、等价LBP模式、旋转不变LBP模式，以及等价旋转不变LBP模式的LBP特征进行提取以及显示(Obtaining LBP features of images: extracting and displaying the original LBP pattern, equivalent LBP pattern, rotation invariant LBP pattern and equivalent rotation invariant LBP pattern of images)

运动检测 检测人体的头部位置、整体位置、滤除影子(Motion detection detect the body and head position, the overall position of the shadow filter)