GABOR 小波代码

在逆向工程中通过测量仪器得到的产品外观表面的点数据集合也称之为点云，通常使用三维坐标测量机所得到的点数量比较少点与点的间距也比较大，叫稀疏点云；而使用三维激光扫描仪或照相式扫描仪得到的点云点数量比较大并且比较密集，叫密集点云。(Data collection point in the surface appearance of the product obtained by reverse engineering measurement instruments, also known as point clouds, usually spaced three-dimensional coordinate measuring machine number of points obtained in relatively small dots are relatively large, called sparse point cloud while the number of point cloud using the three-dimensional laser scanner or camera scanner get bigger and more intensive, called dense point clouds.)

全局法图像垂直条纹去除程序。可以处理高光谱图像、RGB图像，注释详尽。对于倾斜的条纹噪声图像，需要西安进行旋转，再使用该程序去除。内涵循环低速版和无循环高速版，通过比较（处理高光谱数据），高速版的速度比低速版快上近20倍。(Global image vertical stripes removal procedures. Can process the hyperspectral image, RGB image, detailed notes. The stripe noise images of Xi an, need to rotate, then use the program to remove. Connotation of circular low version and loop free high speed version, by comparing (hyperspectral data processing), high speed rate nearly 20 times than the low-speed model.)

说明：  全变分图像去噪 tv_L2 模型 具有非常好边界保持能力的去噪算法(total variational for denosing)

OCR的概念是在1929年由德国科学家Tausheck最先提出来的，后来美国科学家Handel也提出了利用技术对文字进行识别的想法。而最早对印刷体汉字识别进行研究的是IBM公司的Casey和Nagy，1966年他们发表了第一篇关于汉字识别的文章，采用了模板匹配法识别了1000个印刷体汉字。(The concept of OCR in 1929 by the German scientist Tausheck Handel first put forward later, scientists in the United States also put forward ideas of text recognition using technology. In 1966, they published their first article on Chinese character recognition, using template matching method to recognize 1000 printed Chinese characters.)

说明：  能够实现对生物芯片的识别和图像处理，识别有效芯片区域，读取阴性和阳性点分布和数量。(It can realize the recognition and image processing of biochip, identify the effective chip area, read the distribution and number of negative and positive points.)

说明：  用FCM算法实现图像分割(图像源可以是灰度、索引和RGB图像)(FCM image segmentation algorithm (image source can be gray, indexes and RGB images))

图像匹配经典事例。ssda和mad匹配算法。(ssda mad)

对遥感图像进行分类，使用k均值算法,对Indian_pines数据进行分类(Remote sensing image classification, using the k-means algorithm)

本文针对多光谱图像配准中不同光谱图像间存在较大的灰度差异、同一景 物在不同波段表现的特征也各不相同等问题，提出了基于互信息相似性测度的 多光谱图像配准算法。(In this paper, multi-spectral image registration between images in different spectral gray there is a big difference, the same scene in different performance characteristics of band varies and so on, based on mutual information similarity measure for multi-spectral image registration algorithm .)

本程序是用似然比检验的方法进行profile中的变点检测(This procedure is used likelihood ratio test method of change point detection profile)