LMS-of-image

rk3399硬件编解码demo及文档

基于互信息的图像配准源代码，，采用粒子群优化算法可直接使用。 (Based on mutual information image registration source code, using particle swarm optimization algorithm can be used directly.)

说明：  本程序是基于小波和盒维数的车型识别程序，可以选择不同车型，有GUI界面，有图片，有程序，能运行，相信初学者一定能够获益。(This program is based on the wavelet and box dimension of the vehicle type recognition program, you can choose different models, GUI interface, pictures, programs, can run, I believe beginners will benefit.)

压缩感知理论稀疏分解工具箱 内附详细的工具箱使用说明及其大量的例程(Compressed sensing theory of sparse decomposition toolbox toolbox included detailed instructions and a large number of routines)

对李纯明的DRLSE进行了改进 利用各向异性扩散提高了分割弱边缘的能力 改进的高斯滤波代替惩罚项 加快了演化速度 节省了时间(The DRLSE to LiChunMing improved using anisotropic diffusion improve the segmentation of improvement of the ability weak edge gaussian filtering instead of penalty term accelerated evolution speed save time)

去雾处理，可以生成深度图和去雾后的图像 用matlab实现(To fog treatment, can generate a depth map and to fog the image after the realization of using matlab)

基于均值漂移算法实现图像的分割，总共带有三个文件，其中两个是两个子程序(Based on mean-shift image segmentation algorithm, with a total of three documents, two of which are the two subroutines)

实现RGB到HSV空间转换，之后提取H、S、V分量后获取图像的颜色直方图和累计颜色直方图。(Achieve RGB to HSV space conversion, after the extraction of H, S, V components to obtain the image of the color histogram and cumulative color histogram.)

sift算法在cv领域的重要性不言而喻，该作者的文章引用率在cv界是number1.本篇博客只是本人把sift算法知识点整理了下，以免忘记。本文比较早的一篇博文opencv源码解析之(3)：特征点检查前言1 中有使用opencv自带的sift做了个简单的实验，而这次主要是利用Rob Hess的sift源码来做实验，其实现在的opencv版本中带的sift算法也是Rob Hess的，只是稍微包装了下。 下面来做下试验,试验sift代码采用Rob Hess的代码，opencv目前版本中的sift源码也是采用Rob Hess的。代码可以在他的主页上下载：http://blogs.oregonstate.edu/hess/code/sift/ 这里我下载的是windows版本的，并采用Qt做了个简单的界面。(sift algorithm is self-evident the importance of the cv field, the author of the article referenced in the cv sector is number1 this blog I just sift algorithm knowledge compiled under, so as not to forget. This article compares the earlier blog post opencv source code analysis (3): check the preface of the feature points 1 the opencv bring their own sift to do a simple experiment, but this time Rob Hess' s sift source to experiment. In fact, with the opencv version sift algorithm is Rob Hess, only slightly packing the next. Below to do the next test, test sift code using the code of Rob Hess, sift source opencv version of Rob Hess. The code can be downloaded on his home page: http://blogs.oregonstate.edu/hess/code/sift/ here I downloaded the windows version, and using Qt to do a simple interface.)

中值滤波，对3X3有优化，纯C，正对BMP格式(Median filtering, there are optimized for 3X3)