scholar.google.com › citations
Feb 26, 2017 · In this work, we propose a Bayesian nonparametric framework that jointly estimates the number of endmembers, the endmembers itself, and their ...
In this work, we propose a Bayesian nonparametric framework that jointly estimates the number of endmembers, the endmembers itself, and their abundances, by ...
Beta Process. A beta process is characterized by a positive function c and a base mesure B0, and has the following Lévy measure on on ω × [0,1] :.
Hyperspectral imaging is an important tool in remote sensing, allowing for accurate analysis of vast areas. Due to a low spatial resolution, ...
Abstract Hyperspectral imaging can be used in assessing the quality of foods by decompos- ing the image into constituents such as protein,.
We present a Bayesian spectral unmixing algorithm employing a volume constraint and propose an inference procedure based on Gibbs sampling. We evaluate the ...
This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are post-nonlinear ...
We present a Bayesian spectral unmixing algorithm employing a volume constraint and propose an inference procedure based on Gibbs sampling. We evaluate the ...
ABSTRACT. This paper addresses the problem of unmixing hyperspectral images contamined by additive colored noise. Each pixel of the image is.
We propose a hyperspectral image super resolution approach that fuses a high resolution image with the low resolution hyperspectral image using non-parametric ...
Missing: Unmixing | Show results with:Unmixing