Title :
A split bregman method for linear spectral unmixing
Author :
Jianjun Liu ; Zebin Wu ; Zhihui Wei ; Le Sun
Author_Institution :
Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
Linear spectral unmixing is a popular tool to describe the remote sensing hyperspectral data. However, due to the huge size of hyperspectral data and the real-time processing, it needs a faster and more accurate algorithm. In this paper, we present a novel algorithm for linear spectral unmixing based on nonnegative matrix factorization (NMF), referred to as the split bregman method for NMF (SBNMF). The proposed algorithm takes advantage of the fast convergence of split bregman method, and at the same time optimizes the alternating update method, which help it get accurate results faster. The experimental results based on both synthetic mixtures and a real image scene demonstrate the superiority of our proposed algorithm.
Keywords :
geophysical image processing; hyperspectral imaging; matrix decomposition; remote sensing; SBNMF; alternating update method; linear spectral unmixing algorithm; nonnegative matrix factorization; real image scene; real-time processing; remote sensing hyperspectral data; split Bregman method; Abstracts; Conferences; Imaging; Minerals; algorithm; linear spectral unmixing; nonnegative matrix factorization; split bregman;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2012 4th Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3405-8
DOI :
10.1109/WHISPERS.2012.6874249