Moth flame optimization for land cover feature extraction in remote sensing images
Anuraj Singh, Chirag Chhablani, Lavika Goel · 2017
Nature inspired meta heuristics are inspired from the phenomenon which occur in nature. Wide range bio-inspired algorithms provide good results when applied to various kind of applications. In our research we focus on a new nature-inspired algorithm called Moth Flame Optimization(MFO) and adopt it for efficient land cover feature extraction. MFO is based upon the navigation technique of Moths to move in straight line called transverse orientation. Remote sensing is an area which provides enormous benefits for the mankind and a lot of classification techniques have been applied to produce good results. The results are compared to the existing algorithms for the satellite data of Alwar region. We therefore present a model to adopt the MFO algorithm for Image Classification.