Nonlinear Unmixing of Hyperspectral Images: Models and Algorithms
نویسندگان
چکیده
منابع مشابه
Linear and Nonlinear Unmixing in Hyperspectral Imaging
N. Dobigeon*, Y. Altmann, N. Brun and S. Moussaoui University of Toulouse, IRIT/INP-ENSEEIHT, 31071 Toulouse Cedex 7, France School of Engineering and Physical Sciences, Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS, United Kingdom Laboratoire de Physique des Solides, CNRS, Univ. Paris-Sud, Univ. Paris-Saclay, 91405 Orsay Cedex, France Ecole Centrale de Nantes, IRCCyN, UMR CNRS 6597, N...
متن کاملBayesian Nonparametric Unmixing of Hyperspectral Images
Hyperspectral imaging is an important tool in remote sensing, allowing for accurate analysis of vast areas. Due to a low spatial resolution, a pixel of a hyperspectral image rarely represents a single material, but rather a mixture of different spectra. Hyperspectral Unmixing (HSU) aims at estimating the pure spectra present in the scene of interest, referred to as endmembers, and their fractio...
متن کاملPartially Asynchronous Distributed Unmixing of Hyperspectral Images
So far, the problem of unmixing large or multitemporal hyperspectral dataset has been specifically addressed in the remote sensing literature only by a few dedicated strategies. Among them, some attempts have been made within a distributed estimation framework, in particular relying on the alternating direction method of multipliers (ADMM). In this paper, we propose to study the interest of a p...
متن کاملA parallel unmixing algorithm for hyperspectral images
We present a new algorithm for feature extraction in hyperspectral images based on source separation and parallel computing. In source separation, given a linear mixture of sources, the goal is to recover the components by producing an unmixing matrix. In hyperspectral imagery, the mixing transform and the separated components can be associated with endmembers and their abundances. Source separ...
متن کاملUnmixing hyperspectral images using Markov random fields
This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) ...
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 Signal Processing Magazine
سال: 2014
ISSN: 1053-5888
DOI: 10.1109/msp.2013.2279274