MODPCNNFUSION

PIVlab - 时间分辨粒子图像测速（PIV）工具： 一种基于GUI的工具，用于预处理，分析，验证，后处理，可视化和模拟PIV数据。 使用MATLAB网络研讨会进行人脸识别代码： 使用MATLAB在线讲座的人脸识别中的主要演示文件。 Gabor特征提取： 该程序生成一个自定义Gabor滤波器组; 并使用它们提取图像特征。 主成分分析： 用于特征提取； 链码： 基于MATLAB的freeman的曲面轮廓描述(PIVlab - time resolved particle image velocimetry (PIV) tool: A GUI based tool for preprocessing, analysis, validation, post processing, visualization, and Simulation of PIV data. Using MATLAB webinar for face recognition code: The main demo file is used in MATLAB online lectures for face recognition. Gabor feature extraction: The program generates a custom Gabor filter bank and uses them to extract image features. Principal component analysis: For feature extraction; Chain code: Surface contour description of Freeman based on MATLAB)

差影法去背景---部分测试，感觉还行，与大家分享，呵呵差影法去背景(Poor background--- Shadow law to some of the test, I feel also visit to share with you, huh, huh difference method to the background shadow)

展示了汽车行业的应用案例。任务是利用标定的可变形匹配来定位不同方向和位置的车门(3D variable model matching)

本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。 这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘 制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。 从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

毕业论文，运用小波分析对图像进行处理，内附源代码(Thesis, the use of wavelet analysis of the image processing included source code)

用TV算法实现图像去噪，包含TV，PM模型等(in this MTV, the diffusion is along the edge direction of the original noisy image(maybe its smoothed version using a Gaussian filter of small scale),it can preserve edge and suppress staircase very well.)

对各种格式图像实现打开保存旋转的操作的示例工程的说明文档。(images of various formats to achieve preservation of open rotation examples of the operation of the project documentation.)

用方向可调小波变换实现图像边缘提取，包涵实验报告及原图像及处理结果(Steerable Wavelet Transform using edge extraction, bear with lab reports and the original image and processing results)

实现对图像进行二维小波变换，实现图像压缩，并实现图像的压缩传感(Image wavelet transform, to achieve the two-dimensional image wavelet transform for image compression, and compressed sensing to achieve)

压缩感知的第一本书籍，很不错的，各位大牛每人负责一章，可惜的是还不完全，还有几章未编出，希望对你有用(The first book of compressed sensing, very good, you cow each responsible for a chapter, it is a pity that is not fully chapters compile the hope that useful to you)