Total Variation Spatial Regularization for Sparse Hyperspectral Unmixing
نویسندگان
چکیده
منابع مشابه
Manifold regularization for sparse unmixing of hyperspectral images
BACKGROUND Recently, sparse unmixing has been successfully applied to spectral mixture analysis of remotely sensed hyperspectral images. Based on the assumption that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance, unmixing of each mixed pixel in the scene is to find an optimal subset of signatures in a v...
متن کاملTech Report: A Fast Multiscale Spatial Regularization for Sparse Hyperspectral Unmixing
Sparse hyperspectral unmixing from large spectral libraries has been considered to circumvent limitations of endmember extraction algorithms in many applications. This strategy often leads to ill-posed inverse problems, which can benefit from spatial regularization strategies. While existing spatial regularization methods improve the problem conditioning and promote piecewise smooth solutions, ...
متن کاملSparse Hyperspectral Unmixing
Given a set of mixed spectral vectors, spectral mixture analysis (or spectral unmixing) aims at estimating the number of reference materials, also called endmembers, their spectral signatures, and their fractional abundances. A semi-supervised approach to deal with the linear spectral unmixing problem consists in assuming that the observed spectral vectors are linear combinations of a small num...
متن کاملStructured Sparse Method for Hyperspectral Unmixing
Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most existing methods fail to take advantage of the spatial information in data. To overcome this limitation, we propose a Structured Sparse regularized Nonnegative Matrix Factorization (SS-NMF) method from the following two a...
متن کاملHyperspectral Unmixing with Robust Collaborative Sparse Regression
Chang Li 1, Yong Ma 2,∗, Xiaoguang Mei 2, Chengyin Liu 1 and Jiayi Ma 2 1 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China; [email protected] (C.L.); [email protected] (C.L.) 2 Electronic Information School, Wuhan University, Wuhan 430072, China; [email protected] (X.M.); [email protected] (J.M.) * Corresponden...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Geoscience and Remote Sensing
سال: 2012
ISSN: 0196-2892,1558-0644
DOI: 10.1109/tgrs.2012.2191590