matlab图像处理

纹理模式的LBP特征表示及分类原理：就是通过定义一个模板，对于原图像中的每个点，使用该模板进行操作，模板中心点近邻区域对应的图像象素值与中心位置对应的象素值进行比较，且对于不同位置的比较结果赋予不同的权值，从而，变换图像中对应点的值就由模板对应各位置的比较结果之权和表示。(LBP texture pattern feature representation and classification theory: that by defining a template for the original image of each point, use the template to operate, the template center of neighboring regions corresponding to the center of the image pixel values corresponding to the pixel value comparison, and the comparison results for different locations given different weights, and thus, changing the value of the image corresponding points on the template corresponding to each position by the comparison of the results of the right to and express.)

说明：  使用matlab编写的源程序 高斯噪声产生的源代码(prepared by the use of Matlab source Gaussian noise source)

Image Indexing Using Color Correlogram

基于梯度下降的稀疏约束 NMF 算法(NMFsc)，之前pudn上也有类似的，但缺少一个程序，这里面都包括了 (Based on gradient descent sparse constraint NMF algorithm (NMFsc), before the pudn has a similar, but the lack of a program, there are included)

用MTV230做OSD的实际项目源码。希望对您有帮助。(MTV230 do with the actual project OSD source. I hope for your help.)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

说明：  利用HOG算子实现电脑读取图像并进行面部识别与检测(Using hog operator to realize computer reading image and face recognition and detection)

A Image converting Utility to scale the images

图像稀疏表示源代码，实现输入图像的稀疏表示，有MOP,KSVD等算法(Matlab m-file code of Iamge Representation,it can run，contains MOP，KSVD.)

通过高通滤波器实现对图像的锐化处理，能去除不需要的模糊轮廓而加强边缘的对比度。(Image sharpening to achieve through a high-pass filter, and enhance the contrast edges blurred outline can remove unwanted.)