texture

说明：  利用matlab实现图像的直接反投影重建结果(Using Matlab to Realize Direct Back Projection Reconstruction Results of Images)

tutorial压缩感知代码。压缩感知，又称压缩采样，压缩传感。它作为一个新的采样理论，它通过开发信号的稀疏特性，在远小于Nyquist 采样率的条件下，用随机采样获取信号的离散样本，然后通过非线性重建算法完美的重建信号(The tutorial compression-aware code. Compressed sensing, also known as compressed sampling, compressed sensing. It as a new sampling theory, through the development of signal sparsity, in conditions far less than the Nyquist sampling rate, using random sampling for discrete samples of the signal, and then through the non-linear reconstruction algorithm perfect reconstructed signal)

图像球面化，对于输入的图片进行球面变换达到图形变形的效果(Spherical image of, for input images to spherical transformation to achieve the effect of graph distortion)

说明：  一种实现超分辨率图像处理的新算法,本算法在综合前人算法的基础上，做了很大改进。很适合图像处理。(An implementation of the new super-resolution image processing algorithms, the algorithm in integrated algorithm based on the predecessors has done a lot of improvements. Very suitable for image processing.)

包含五个文件夹。 （1）MATLAB程序：其中包含10余个MATLAB程序或（函数）的源代码。程序中所作的注释，与书中关于对应算法的描述是一致的 （2）二值图像：其中的图像可供形态学图像处理实验用，也可通过提取对象的边界，供曲线演化实验使用。 （3）灰度图象和彩色图像：其中的图像，可以作为图像分割，平滑滤波，反差增强，彩色增强以及图像放大等实验的素材。 （4) 视频剪辑：，"two_cells"是采用改进的变分水平集方法，实现GAC模型图像分割的演化过程；"denoissing"是利用P_M方程，对图像平滑去噪的演化过程 "curve_linear_heat_flow"是利用FT实现的闭合曲线的线性热流演化过程。 (These codes are focused on PDE image processing)

基于svd的数字水印，信噪比比较高(Svd based digital watermarking, can also signal to noise ratio is relatively high)

说明：  用于绘制节理面粗糙度风玫瑰图的Matlab程序，包含节理面粗糙度各向异性的案例数据！(Matlab program for drawing wind rose diagram of joint surface roughness, including case data of joint surface roughness anisotropy)

源点定位程序，可用于检测连通域等功能，代码是c/c++的，放心使用。(Source point positioning procedures, can be used to detect other functions connected domain, the code is c/c++, and ease of use.)

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. )

实现了迭代盲反卷积的图像去模糊，自己写的代码，没有调用matlab已有函数(Iterative blind deconvolution of images blurred, write your own code, without calling matlab existing function)