cfa_laroche

对变形的条纹图像进行傅立叶变换得到二维频谱图并提取基频(Fourier transform in deformation stripes image two-dimensional spectrum and extract the fundamental frequency )

基于纹理及光谱信息融合的遥感图像分类方法研究，硕士论文，有关纹理和遥感图像分类很好的学习素材(Texture and spectral information based on the integration of remote sensing image classification method, master' s thesis, the classification of remote sensing image texture and good learning material)

FPGA数字图像处理实现均值滤波，并且仿真将生成图片写出TXT格式以便使用MATLAB查看(Mean filter is realized by digital image processing in FPGA, and the generated image is written in TXT format for viewing with MATLAB.)

说明：  平台基于visual studio2015，使用opencv函数实现双边滤波，进行图像处理(bilateral Filter based on opencv)

针对遥感图像可控参数误差造成的图像模糊，进行模糊核估计(Remote sensing images for image blur caused by controllable parameter error, blur kernel estimation)

说明：  实验室自己用的fbp重建算法，基于C语言，亲测可用。上有个人C盘名称信息请删除(Ct reconstruction fbp)

用lbp实现纹理特征提取，并分类说明: 一共有三个m文件，一个是lbp.m, 存放主要的lbp算法， 一个是getmapping,用以做算法的辅助函数， 一个是lbptest.m,存放着测试代码。 这三个文件需要放到同一个文件夹，并在文件夹中添加相应的图片， 具体的图片名字见lbptest.m的代码，运行lbptest.m可以查看结果。代码最后给出效果图 这三个文件是最传统的LBP方法，有256种。(With lbp achieve texture feature extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

SURF算法为SIFT算法的改进，运算速度得到了很大的提高。本资料为基于MATLAB的SURF算法实现，对图像匹配的研究方向会有一定帮助。(SURF algorithm SIFT algorithm, computing speed has been greatly improved. MATLAB based on the information of the SURF algorithm for image matching the direction of the research will certainly help.)

检测皮肤代码。主要包括图像读入，大小变换，格式转换，图像滤波，颜色空间转换，皮肤模型，去除少像素连同区域以及膨胀作用(face detection based on skin model)

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。 该方法于 1999 年由 David Lowe 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004 年再次经 David Lowe 整理完善后发表于 International journal of computer vision（IJCV） 。截止 2014 年 8 月，该论文单篇被引次数达 25000 余次。(来自百度)(SIFT, namely Scale-invariant feature transform (SIFT), is a description used in the field of image processing. This description has scale invariance and can detect key points in images. It is a local feature descriptor. This method was first published by David Lowe at the International Conference on Computer Vision (ICCV) in 1999 and published in the International Journal of Computer Vision (IJCV) in 2004 after it was sorted out and perfected by David Lowe again. As of August 2014, more than 25,000 citations have been cited. (From Baidu))