CarroisGothicSC-Regular

压缩感知和超分辨率论文，关于如何将低分辨率的图像如何重建成高分辨率图像，很有用(compressed sensing and super resolution)

说明：  这是冈萨雷斯经典教材数字图像处理（MATLAB版）的所有源代码，很辛苦才获得的(This is a classic textbook Gonzalez Digital Image Processing (MATLAB version) all the source code, it is hard before they are allowed to)

高斯有色噪声，有色噪声的谱估计及其在雷达中的应用(gauss noise)

中南大学数字图像处理上机实验指导书及参考答案，全部由本人编写，在MATLAB 6.5上运行通过。包括图像变换及频域滤波，空间域图像增强，图像边缘检测及参考图片，比网上流传的好的多，是学习图像处理的基础。(Zhongnan University of digital image processing on the experimental guide and reference book answers all prepared by me, MATLAB 6.5 to run through. Image Transform and including the frequency domain filtering and spatial domain image enhancement, edge detection and reference photographs, spread over the Internet much more study is the basis of image processing.)

功能：去模糊/去马赛克 A joint demosaicking-zooming scheme for single chip digital color cameras(2007)论文以及源码(Function: to blur/demosaicing A joint demosaicking-zooming scheme for single chip digital color cameras (2007) paper and source code)

做图像轮廓提取的应该都听说果GVF这个概念，也难免有没听过的，不过可以看看这个程序(Does the image contour extraction of GVF should have heard the concept of fruit, but also inevitably have heard, but can look at this process)

混合像元分解，是定量遥感中非常重要的组成部分之一，在反演地表参数时是必须要考虑的因素之一，文中罗列了分解的一些方法(mixed pixel decomposition, is the quantification of remote sensing very important component of one of the the inversion of surface parameters is to be considered one of the factors, the paper listed some of the decomposition method.)

图像频域滤波，实现图像频域滤波，加深对频域图像增强的理解(Image frequency domain filtering, image frequency domain filtering, to deepen understanding of the frequency-domain image enhancement)

图像格式转换例程源码，程序主要结合易语言图像格式转换支持库，可以将某些图象文件的格式转换到其它图象文件的格式(Image format conversion routines source, the program mainly with easy language support library image format conversion, you can convert the image file format to some other image file formats)

该代码是基于学习的超分辨率重建，此算法是在线字典学习，字典的训练与稀疏表示与重建同时进行。(This code is based on the study of super-resolution reconstruction, this algorithm is learning online dictionaries, dictionaries of training and sparse representation and reconstruction simultaneously.)