In this work we present a software simulator for the performance evaluation of the NDSA (Normalized Differential Spectral Absorption) method at global scale assuming a realistic s...
The main purpose of this paper is to describe available (HPC)based implementations of remotely sensed hyperspectral image processing algorithms on multi-computer clusters, heterog...
A novel STAP algorithm based on sparse recovery technique, called CS-STAP, were presented. Instead of using conventional maximum likelihood estimation of covariance matrix, our met...
Ke Sun, Hao Zhang, Gang Li, Huadong Meng, Xiqin Wa...
Most available methods for endmember extraction use the convexity of the data structure and consider the vertices of the data as the purest pixels. Such methods do not consider th...
Spectral mixture analysis is an important task for remotely sensed hyperspectral data interpretation. In spectral unmixing, both the determination of spectrally pure signatures (e...