期刊论文

Mei, Xiaoguang

英文

Remote Sensing

2072-4292

2019

11

20

2434-

10.3390/rs11202434

Conceptualization, Q.J. and X.M.; Funding acquisition, Y.M.; Methodology, Q.J.; Resources, Q.J.; Software, Q.J.; Supervision, Y.M., E.P., C.S., F.F., and J.H. and H.L.; Writing—original draft, Q.J.; Writing—review editing, Q.J. and X.M. This work was supported by the National Natural Science Foundation of China under Grant nos. 61805181, 61773295, 61601397, and 61903279.

本校为其他机构

In recent years, endmember variability has received much attention in the field of hyperspectral unmixing. To solve the problem caused by the inaccuracy of the endmember signature, the endmembers are usually modeled to assume followed by a statistical distribution. However, those distribution-based methods only use the spectral information alone and do not fully exploit the possible local spatial correlation. When the pixels lie on the inhomogeneous region, the abundances of the neighboring pixels will not share the same prior constraints. Thus, in this paper, to achieve better abundance estim...