MS_MATLAB

用C charp编写的图像滤镜效果，包括源代码。(Image filter effects)

说明：  本压缩包主要包括数字图像处理——使用MATLAB分析与实现的源代码(This compression package mainly includes digital image processing - using MATLAB analysis and implementation of the source code)

灰度差分统计法提取图像纹理特征，包括平均值，对比度，熵，等特征，matlab函数，直接接使用，无需修改，中文注释，通俗易懂(Gray difference statistical method is used to extract texture features of image, including mean value, contrast, entropy, etc., matlab function, directly used without modification, Chinese annotation, and easy to understand)

CV模型源代码, 用水平集进行图像分割。一个经典的算法。(matlab source code of CV model)

surf算法对图像的配准实时的取证，经本人验证，该程序好用无误，可放心使用(surf algorithm for image registration in real time forensics, after I verify that the correct program easy to use, ease of use)

背景减除的完整算法，《A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection》作者源代码(The "src" folder contains all of the source code. To run the program, follow these simple steps: 1. Start MATLAB and ensure the "src" folder is your current working directory. 2. Edit "bs.m" and "classify.m" so that the file paths point to the proper directories as specified. 3. In the MATLAB environment type "bs" which will train the background model from the sequence you specified in (2). 4. In the MATLAB environment type "classify" which will classify the sequence of images you specified in (2). 5. Now the classified images should be saved to disk in the folder you specified in (2).)

基于先验信息和射影几何变换的车牌图像矫正 对于图像矫正还是有帮助的(License plate image correction based on a priori information and projective geometry transform for image correction or help)

匹配算法，可以完美运行，对于初学者有着很好的参考价值(Matching algorithm, can be a perfect run, has a very good reference for beginners)

目标跟踪源码，MATLAB编写的！里面包含三个子函数！(target tracking source, MATLAB! Functions of which contains three!)

实现简单图像处理，包括256色转灰度图、Hough变换、Walsh变换、中值滤波、二值化变换、亮度增减、傅立叶变换、反色、取对数、取指数、图像平移、图像旋转、图像细化、图像缩放、图像镜像、均值滤波、对比度拉伸、拉普拉斯锐化（边缘检测）、方块编码、梯度锐化、灰度均衡、直方图均衡、离散余弦变换、维纳滤波处理、逆滤波处理、阈值变换、高斯平滑。(simple image processing, including color to grayscale 256, the Hough transform, Walsh transform, Median filtering, binary conversion, brightness changes, Fourier transform, and color-from the few to admit index, image shifting, image rotation, refined images, image scaling, image mirroring, mean filtering, contrast stretching, Laplacian sharpening (edge detection), block codes, Sharpening gradient, gray balance, histogram equalization, discrete cosine transform, Wiener filter, reverse filtering, threshold transform, Gaussian smoothing.)