final-test-code

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.)

改进的图像分割算法：运用SLIC超像素分割和DBSCAN聚类算法相结合的方法实现图像分割(Image Segmentation using SLIC SuperPixels and DBSCAN Clustering)

实现运动模糊图像的非盲卷积 分区域去模糊 有用(Implementation of motion blurred image blind deconvolution is useful to fuzzy areas)

Real-time foreground–background segmentation using codebook model 了解码书进行图像处理(背景与前景)的原理，可以从该文章中获得有益的参考价值(Real-time foreground–background segmentation using codebook model A practical paper for knowing of image processing theory(about foreground-background) by codebook)

在IDL中运行，可以将多光谱、高光谱等多波段影像拆分为为单一波段影像(It works in IDL and it can split multibands into single band)

图像修复中基于一幅图像的改进的Criminisi方法的近，算法的时间大大提高，修改效果也不错。(Time based on the improved image Criminisi near algorithm greatly improve image repair, modify the effect is also good.)

对于存在块效应图像进行质量评价 matlab程序 比较适合初学者(For the existence of blocking matlab image quality evaluation procedures are more suitable for beginners)

单幅图象的暗原色先验去雾改进算法，能够很好地改进天空或明亮部分色彩失真问题，matlab代码注解详细，能很好地帮助理解算法过程。(improvement of a single image dehazing algorithm using dark channel prior,solving the problem of color distortion of sky and bright part!Having a good explain of the code,which could be helpful to understand the processing of the algorithm! )

说明：  在IDL中将.nc格式的数据读取并绘图，文件夹中附有示例数据。(Reading and drawing data in.Nc format in IDL)

一种基于non-sample的纹理合成demo，程序性能还有待优化，效果还不错.(texture synthesis demo.)