Threshold-segmentation

整理了五种多曝光图像融合的代码，用于图像处理，图像去雾，有英文介绍(Five kinds of multi-exposure image fusion codes are sorted out.For image processing, image defogging, with English introduction)

用分水岭算法对三维模型进行分割处理。可以实现对三维模型的有意义分割。(Using three-dimensional model of the watershed algorithm to be dealt with separately. Three-dimensional model can achieve meaningful partition.)

利用马尔科夫随机场对图像进行语义分割，通过ICm求解参数，可以运行，对初学者有较好的借鉴作用(Using Markov random field to semantic segmentation of images, through ICm solution parameters, can run, for beginners have a good reference)

用于计算两幅图片之间的峰值信噪比，从而衡量图片重建质量(It used to calculate the peak signal to noise ratio between the two pictures, which measure the quality of the reconstructed image)

Implementations of image processing algorithms(This project can be built by Visual Studio 2012. Project description file included. Currently it is for Windows only.)

自行编写的逆投影变换，可实现图像坐标系到世界坐标系的转换，从实现鸟瞰变换。(the IPM ,which is completed by me, is able to achieve the transformation between the image coordinates and world coordinates )

利用条件随机场实现的对文本的分类和识别.能在不同参数条件下实现分类(With the use of conditions to achieve the airport on the text classification and identification. Can realize different parameters under the conditions of classification)

说明：  在这个知识库中，图形信号处理的一些有趣的特性被表示出来。演示通过经典信号处理和图形信号处理对一维和二维欧几里得域信号应用低通滤波器，比较两种方法的结果。在此基础上，验证了图形信号处理的工作机制。此外，还描述了在非欧几里得域上滤波信号的示例。(In this repository, Some fascinating features of Graph Signal Processing were represented. Demos incudes applying a low-pass filter on both 1D and 2D euclidian domain signal by classical signal processing and also Graph signal processing to compare both results are the same. Within that way, we will validate the working mechanism of Graph Signal Processing. In addition to this, an example of filtering a signal on the non-euclidian domain was also represented.)

基于小波变换的图像融合源程序，通过调试，能直接使用。(Image fusion based on wavelet transform source code through the debugger can be used directly.)

说明：  遥感信息工程学院遥感原理与应用课程实习植被指数(Vegetation Index of Remote Sensing Principle and Application Course Practice)