Name
Abstract | ||
|---|---|---|
Conventional image fusion algorithm, such as IHS, SVR, PCS, etc., may show some defects in inheriting the higher-spectral
information embedded in the original lower-spatial resolution MS image. A fusion method based on spectral mixture analysis
(FSMA) was proposed in previous study, which has potential in solving this problem. While published results are limited to
well-behaved simulated data where the endmembers are known a priori and the FSMA method will not work well when applying to real remotely sensed images because the estimated reflectance ranging
in panchromatic band derived from MS bands cannot be treated as the real panchromatic values. In this paper, an improved image
fusion method based on spectral mixture analysis (IFSMA) is proposed, in which the original FSMA method was extended to real
remotely sensed images by modifying the objective function of the constrained nonlinear optimization expressions. It was compared
with the original FSMA, Zhang’s SVR, PCS and IHS method, and results indicated that the IFSMA method was superior to other
methods in preserving the spectral and spatial information. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s11432-010-3118-6 | SCIENCE CHINA Information Sciences |
Keywords | Field | DocType |
objective function,image fusion,spatial information,nonlinear optimization,spatial resolution | Spatial analysis,Image fusion,Expression (mathematics),Control theory,Nonlinear programming,A priori and a posteriori,Fusion,Ranging,Artificial intelligence,Computer vision,Pattern recognition,Panchromatic film,Mathematics | Journal |
Volume | Issue | ISSN |
53 | 6 | 18622836 |
Citations | PageRank | References |
2 | 0.37 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Yang | 1 | 2 | 1.72 |
| Jin Chen | 2 | 259 | 31.87 |
| Bunkei Matsushita | 3 | 68 | 9.80 |
| Miaogen Shen | 4 | 4 | 2.55 |
| Xuehong Chen | 5 | 47 | 11.12 |