chap9

说明：  Z. Liang, J. Xu, D. Zhang, Z. Cao, L. Zhang, "A Hybrid L1-L0 Layer Decomposition Model for Tone Mapping," in CVPR 2018.

cvpr2012_oral On Multiple Foreground Cosegmentation(In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo sets where a finite number of K foregrounds of interest repeatedly occur over the entire photo set, but only an unknown subset of them is presented in each image. This contrasts the classical cosegmentation problem dealt with by most existing algorithms, which assume a much simpler but less realistic setting where the same set of foregrounds recurs in every image. We propose a novel optimization method for MFC, which makes no assumption on foreground configurations and does not suffer from the aforementioned limitation, while still leverages all the benefits of having co-occurring or (partially) recurring contents across images. Our method builds on an iterative scheme that alternates between a foreground modeling module and a region assignment module, both highly efficient and scalable. In part)

白噪化处理，这是高光谱图像数据降维的前预处理，也称为球化，在数据降维中必须用到(White noise process, which is pretreatment hyperspectral image data dimensionality reduction, also called the ball in the data dimensionality reduction must be used)

说明：  人工智能 caffe 用与ssd yolo(Artificial intelligence SSD Yolo)

image compression using sphit algorithm

这是一个实现从RGB到HSI的互换的程序,你可以将一个你所喜欢的(This is an implementation from RGB to HSI swap program, you can take a you like)

简单水印制作源码,程序结合易语言扩展界面支持库，实现了加载水印效果图和设置水印效果的功能(Simple watermarking source code , the program combined with easy language support library expansion interface , to achieve a load diagram and set watermark watermark function)

实现文章“Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries”中的降噪算法(Realize the article " Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries" in the noise reduction algorithm)

说明：  基于ADMM的TV正则化最小化稀疏重建算法(TV Minimization Sparse Reconstruction Algorithms Based on ADMM)

用ＷＰＦ写一个简单的转盘