unmixing

Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution

代码：GitHub-danfenghong/ECCV2020_CUCaNet:Cross-AttentioninCoupledUnmixingNetsforUnsupervisedHyperspectralSuper-Resolution,ECCV,2020.(PyTorch)https://github.com/danfenghong/ECCV2020_CUCaNet模型数学支撑：基本假设：X图

CCRJ·2022-12-05 22:25

Hyperspectral unmixing阅读笔记---整理中

Hyperspectralunmixing阅读笔记---整理中为什么搞Hyperspectralunmixing?线性混合模型Mixturemodel基于LMM的经典解混思路purepixel模型HyperspectralunmixingalgorithmAlgorithmforpurepixelConvexGeometry（CG）Nonnegativematrixfactorization（NM

SITOZ·2022-11-30 13:32

Nonconvex-Sparsity and Nonlocal-Smoothness-Based Blind Hyperspectral Unmixing

J.Yao,D.Meng,Q.Zhao,W.CaoandZ.Xu,"Nonconvex-SparsityandNonlocal-Smoothness-BasedBlindHyperspectralUnmixing,"inIEEETransactionsonImageProcessing,vol.28,no.6,pp.2991-3006,June2019,doi:10.1109/TIP.2019.2

m0_51414342·2022-11-30 13:55

Generalized Morphological Component Analysis for Hyperspectral Unmixing

X.Xu,J.Li,S.LiandA.Plaza,"GeneralizedMorphologicalComponentAnalysisforHyperspectralUnmixing,"inIEEETransactionsonGeoscienceandRemoteSensing,vol.58,no.4,pp.2817-2832,April2020,doi:10.1109/TGRS.2019.295

m0_51414342·2022-11-30 13:55

Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing

F.Xiong,J.Chen,J.ZhouandY.Qian,"Superpixel-BasedNonnegativeTensorFactorizationforHyperspectralUnmixing,"IGARSS2018-2018IEEEInternationalGeoscienceandRemoteSensingSymposium,2018,pp.6392-6395,doi:10.110

m0_51414342·2022-11-30 13:17

目标检测——day56 Unmixing_Convolutional_Features_for_Crisp_Edge_Detection（用于清晰边缘探测的卷积特征分解）

Unmixing_Convolutional_Features_for_Crisp_Edge_Detection2METHODOLOGY2.2TheTracingLoss2.2.1WeightedCrossEntropy2.2.2FeatureUnmixingbyTracingBoundaries2.3Context-AwareFusionBlock3EXPERIMENTSANDANALYSIS3

qq_43537420·2022-11-28 05:18

论文阅读：Fast Color Segementation

FastColorSegementation发表于CVPR2020，主要是对之前的一篇图像软分割的论文（参见：论文回顾：Unmixing-BasedSoftColorSegmentationforImageManipulation

Researcher-Du·2022-11-26 15:33

Distributed Blind Hyperspectral Unmixing via Joint Sparsity and Low-Rank Constrained Non-Negative Ma

C.G.Tsinos,A.A.RontogiannisandK.Berberidis,"DistributedBlindHyperspectralUnmixingviaJointSparsityandLow-RankConstrainedNon-NegativeMatrixFactorization,"inIEEETransactionsonComputationalImaging,vol.3,n

m0_51414342·2022-11-22 06:04

Region-Based Structure Preserving Nonnegative Matrix Factorization for Hyperspectral Unmixing

L.Tong,J.Zhou,X.Li,Y.QianandY.Gao,"Region-BasedStructurePreservingNonnegativeMatrixFactorizationforHyperspectralUnmixing,"inIEEEJournalofSelectedTopicsinAppliedEarthObservationsandRemoteSensing,vol.10

m0_51414342·2022-11-22 06:34

Superpixel-based Noise Robust Sparse Unmixing of Hyperspectral Image （2021）

基于超像素的高光谱图像噪声鲁棒稀疏解混摘要:高光谱图像稀疏解混(SU)是一种半监督方法，其目标是找到预先已知的光谱库的最优子集来表示高光谱图像中的每个像素。然而，现有的SU方法大多不能充分利用HSI中的空间信息和混合噪声。为此，我们提出了一种混合噪声下基于超像素的噪声鲁棒SU方法(SNRSU)。首先，我们对HSI的第一主成分进行超像素分割(SS)以提取均匀区域。然后，在最大后验框架下，基于稀疏表示

m0_51414342·2022-11-22 06:33

Structured Discriminative Nonnegative Matrix Factorization for hyperspectral unmixing

X.Li,J.Zhou,L.Tong,X.Yu,J.GuoandC.Zhao,"StructuredDiscriminativeNonnegativeMatrixFactorizationforhyperspectralunmixing,"2016IEEEInternationalConferenceonImageProcessing(ICIP),2016,pp.1848-1852,doi:10.

m0_51414342·2022-11-22 06:53

送面膜结果

昨晚文末小互动实在太热烈了，所以临时增加了两位获奖者获奖名单评论头名的：洋气小波尼还有三位随机抽取的庞友：Keman、xiwenluoswy、胡君看完Unmixing了吗？

野兽派娱乐·2016-04-29 00:00

线性波谱分离

2009年4月6日 20:40:31 envi——spectral——mapping methods——linear spectral unmixing 线性波谱分离即进行混合像元分解

·2009-04-06 22:00

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