A Novel Multitemporal Image-Fusion Algorithm: Method and Application to GOCI and Himawari Images for Inland Water Remote Sensing
Yulong Guo, Changchun Huang, Yali Zhang, Yuan Li, Weiqiang Chen
Abstract
A spectral-temporal-unmixing-based multitemporal image fusion (MTIF) algorithm is proposed to fuse Geostationary Ocean Color Imager (GOCI) and Himawari images. The algorithm was applied to two data sets. The fusions are quantitatively and qualitatively compared with four widely used algorithms. The results show that the MTIF algorithm performs better using both evaluation indexes and visual comparisons. For optical complex water monitoring, the MTIF - derived chlorophyll-a concentration (${C} _{{\text {chla}}}$ ) map has better spatial detail and temporal trends compared with the other algorithms. For cloudy images, the MTIF algorithm can estimate part of the under cloud water reflectance information: when there are more than 32.6 cloud-free pixels in the current study area, the MTIF algorithm can successfully recover the under cloud information. The MTIF algorithm has great potential to advance the monitoring of optical complex inland water.