压缩感知图像重构的算法

多分辨率灰度和旋转不变纹理分类与定位二进制模式(multiresolution gray scale and rotation invariant texture classification with location binary patterns )

掌纹识别代码，内有详细代码以及train的图(Palmprint recognition code, there are detailed code and train diagram.cation code)

图像融合里边剪切波变换方法的工具箱，欢迎下载(Shear wave transformation method for image fusion in the toolbox, welcome to download)

用matlab仿真，研究不同阈值降噪后的效果，使用penalty阙值降噪后信号，使用Birge_Massart阙值降噪后信号，使用缺省阙值降噪后信号。(Using matlab simulation to study the different threshold noise reduction effect, the use of penalty threshold denoised signal after noise reduction using Birge_Massart threshold signal, use the default threshold signal after noise reduction.)

张正友相机标定源码，数据及图片，包含说有文件，能正常运行(zhang s calibration)

六种图像增强的方法，线形反锐化掩膜方法，直方图均衡等。(6 kinds of image enhancement methods, linear unsharp mask method, such as histogram equalization.)

本程序采用水平集方法，演示了一个心形曲线在曲率力的作用下，逐渐消逝的过程。(This procedure uses the level set method, shows the process of a heart-shaped curve s disappearing under the force of the curvature.)

图像质量评价的一个重要的指标：平均结构相似度（MSSIM），比PSNR有更好的性能，并且计算简单。(Image quality assessment is an important indicator: Average structural similarity (MSSIM), better than the PSNR performance, and easy to compute.)

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. )

说明：  基于Retinex算法的单尺度图像增强算法。(An image enhancement algorithm based on RETINEX theory.)