新建文件夹

说明：  matlab图像融合，对一幅图像的RGB三通道分别做不同的处理，然后重新融合(Matlab image fusion, an image of RGB three channels to do different processing, and then re-fusion)

乳腺X线图像增强质量评价的ＭＡＴＬＡＢ程序，这里使用对比度和ＤＳＭ两种评价方法对乳腺Ｘ线图像增强方法的优劣做一个客观的评价。(Breast X-ray image enhancement the quality assessment of the MATLAB program, where the use of contrast and DSM two evaluation methods to make an objective assessment of the pros and cons of breast X-ray image enhancement method.)

Finding MSER regions and Canny edges in natural images

边缘保留平滑滤波器的实现代码，用于图形图像处理问题(Edge-preserving smoothing filter to achieve code for graphics and image processing problems)

说明：  nsct图像处理代码，关于图像融合方面的(NSCT image processing code, about image fusion)

对于一个二值图像骨架化之后进行边缘平滑，滤波，效果非常不错，适合于任何二值图片(After a binary image is skeletonized, it is smoothed and filtered. The effect is very good. It is suitable for any binary image.)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)

寻找最低像素值的matlab实现：通过图像矩阵的循环查找，能实现最低像素值的快速寻找(Matlab find the lowest pixel value to achieve: to find the cycle through the image matrix, to achieve the minimum pixel value Quick Find)

基于opencv的Kinect深度图像的去噪，滤波(Opencv based Kinect depth image denoising, filtering)

图像交互是分割 graph cut,实现交互式分割，并且可以连续分割(Interactive image is split graph cut, to achieve interactive segmentation, and can be continuously split)