Visual Analysis for Multi-Spectral Images Comparisons

Abstract

The analysis for images helps people to gain insights by extracting the inner features and variances between them. However, it is hard to analyze the underlying events further without users participation. We proposes a visual analytic system based on collaborative tagging techniques to allow users to identify features and changes from multi-spectral images. We evaluate our system with mini challenge 3 of VAST Challenge 2017. The exploration results validate the efficiency and effectiveness of our system.