geometric_transformation

这个算法包实现了从多幅拥有共同结构的图像里提取出共同形状的骨架。( This package implements the algorithm for Sketching the Common as described in: Shai Bagon, Or Brostovsky, Meirav Galun and Michal Irani "Detecting and Sketching the Common", CVPR 2010)

IDL中的批量重采样，可以省很多时间，根据自己的需求，采样成不同分辨率的图像。(IDL in batch resampling, you can save a lot of time, according to their needs, a different sampling resolution images.)

利用libsvm对遥感影像进行分类，需在已经编译了libsvm的环境进行(Using libsvm to classify remote sensing images)

基于JPG2000图像的超分辨率重建的matlab程序(JPG2000-based super-resolution reconstruction of image matlab program)

区域生长法获取图像边界 必须有种子 可以有很多方法 这里直接鼠标点击(Region growing method to obtain the image the border must have a lot of methods of seed can have a direct mouse click here)

VB像素光影跟踪（图像渲染）工具,有需要的就下载吧。(VB Tracking pixel lighting (image rendering) tools, there is a need to download it.)

编译好的tesseract 4.0库 for VS2015 (含lib、dll和头文件)，另附一个tessreact 4.0进行图片识别的示例程序，并给出运行具体配置方法！

寻找最低像素值的matlab实现：通过图像矩阵的循环查找，能实现最低像素值的快速寻找(Matlab find the lowest pixel value to achieve: to find the cycle through the image matrix, to achieve the minimum pixel value Quick Find)

图像加密算法本文讨论了基于现代密码体制的图像加密、基于矩阵变换的图像加密、基于混沌的图像加密、基于秘密分存的图像加密、基于频域的图像加密、基于ＳＣＡＮ 语言的图像加密和基于 ＤＮＡ 计算的图像加密等主流图像加密算法的加密原理、优缺点和最新进展(This paper discusses image encryption algorithm based on modern cryptography, image encryption based on matrix transform, image encryption based on chaotic image encryption based on secret sharing based on frequency domain image encryption, image encryption, image encryption based on SCAN language and DNA based on the calculation of image encryption and other mainstream image encryption algorithm, encryption principle the advantages and disadvantages and the latest progress)

孔径雷达图像固有的相干斑噪声严重降低了图像的可解译程度，影响了后续目标检测、分类和识别 等应用。因此，SAR图像的相干斑抑制问题一直是SAR图像应用的重要课题之一。一个理想的去斑算法应该在平 滑的同时保持图像的边缘等细节不受损失，目前存在各种各样的算法，但没有一种方法能够完美的满足这一要求。 本文对SAR图像的相干斑抑制问题进行了全面系统的研究，分析了相干斑的形成原因，总结了目前存在的相干斑 抑制算法的主要思路，介绍了具有代表性的算法，并对各种算法的性能进行了定性分析和比较，给出了去斑算法定 量评估方法(The inherent speckle noise of the aperture radar image seriously reduces the degree of interpretation of the image, and affects the detection, classification and recognition of the subsequent targets. And other applications. Therefore, the problem of speckle suppression in SAR images has been one of the most important topics in the application of SAR images. An ideal speckle algorithm should be flat At the same time, the details such as edges of images are not lost. There are various algorithms at present, but none of them can satisfy this requirement perfectly.)