The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper
AbstractImage fusion is a useful tool in integrating a high-resolution panchromaticimage (HRPI) with a low-resolution multispectral image (LRMI) to produce a highresolutionmultispectral image (HRMI). To date, many image fusion techniques have beendeveloped to try to improve the spatial resolution of the LRMI to that of the HRPI with itsspectral property reliably preserved. However, many studies have indicated that thereexists a trade- off between the spatial resolution improvement and the spectral propertypreservation of the LRMI, and it is difficult for the existing methods to do the best in bothaspects. Based on one minimization problem, this paper mathematically analyzes thetradeoff in fusing remote sensing images. In experiment, four fusion methods are evaluatedthrough expanded spectral angle mapper (ESAM). Results clearly prove that all the testedmethods have this property. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Chen, S.; Su, H.; Zhang, R.; Tian, J.; Yang, L. The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper. Sensors 2008, 8, 520-528.
Chen S, Su H, Zhang R, Tian J, Yang L. The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper. Sensors. 2008; 8(1):520-528.Chicago/Turabian Style
Chen, Shaohui; Su, Hongbo; Zhang, Renhua; Tian, Jing; Yang, Lihu. 2008. "The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper." Sensors 8, no. 1: 520-528.