Improving Map-Based Post-Disaster Management System Using Gaussian Multisource Data Fusion Algorithm

Abstract

It is critical to provide an efficient and accurate information system in the post-disaster phase for individuals' in order to access and obtain the necessary resources in a timely manner, but current map based post-disaster management system will provide all emergency resource list without filtering that will lead to high energy consumed calculation. In this study, we improved the map combining disaster map to initial GIS based map which located the target area considering the influence of disaster. First, all initial map and disaster map will be under Gaussian transformation while we acquired the histogram of all map pictures. And then all pictures will be under discrete wavelet transform (DWT), a Gaussian fusion algorithm was applied in the DWT pictures. Second, inverse DWT (iDWT) was applied to generate new map for post-disaster management system. Finally, simulation works were proposed and the results showed the effectiveness of the proposed method by comparing with other fusion algorithms, such as mean-mean fusion and max-UD fusion through the evaluation indices including entropy, spatial frequency (SF) and image quality index (IQI).