lowcomplexitymc

说明：  SIFT用于图像全景拼接的源码，内附算法描述，很好用。(SIFT source code for image panorama stitching, containing algorithm descriptions, easy to use.)

高光谱图像的分类，适合各种光谱数据或者RGB图像。只需要调整输出路径就好了。(Hyperspectral image classification, for a variety of spectral data or RGB images. Only you need to adjust the output path just fine.)

我自己做的一个bmp文件进行24位真彩转256灰度和二进制的程序，并能用sobel算法，识别物体的边界。 (I myself make a bmp file for 24-bit true color to 256 gray-scale and binary procedures and sobel algorithm can be used to identify object boundaries.)

说明：  基于区域的分裂合并图像分割方法，包含三个m文件，predicate是分裂合并准则代码，split_test用于检测是否需要分裂，splitmerge用于分裂合并(Region Based Split Merge image segmentation method, including three m files, predict is the splitting and merging rule code, split_ Test is used to detect whether splitting is needed, and splitmerge is used for splitting and merging)

基于拓展RPC模型的多源卫星遥感影像几何处理 转化程序(RPC model-based development of multi-source remote sensing image processing conversion process geometry)

说明：  基于开源计算机视觉库OpenCV的图像处理基于开源计算机视觉库OpenCV的图像处理(Based on open source computer vision library OpenCV image processing based on open source computer vision library OpenCV image processing)

冈萨雷斯第二版数字图像处理工具箱函数集Matlab源程序(Gonzalez, the second edition of Digital Image Processing Toolbox Matlab source code function set)

Matlab图像处理中的Harris角点提取算法， 代码中有详细的解说，方便阅读。 (Matlab Image Processing of Harris corner extraction algorithm, the code has a detailed explanation, easy reading.)

图像分割是图像分析的关键步骤，而水平集方法是图像分割的一项热门方法，它有着许多算法不具有的优点，尤其可用于分割背景复杂信息难以提取的医学图像。这里是一些水平集分割图像的matlab的实现例子，希望可以帮到大家。(Image segmentation is the key step of image analysis, while the level set method is a popular image segmentation method, it has many advantages that the algorithm does not have, especially can be used for medical image segmentation of complex background information is difficult to extract. Here is some level set segmentation image matlab example, I hope we can help you.)

说明：  对于双基地SAR，基于IDL语言使用BP算法进行成像，以及显示回波信号。(For Bistatic SAR, BP algorithm is used to image and display echo signal based on IDL language.)