Sub-pixel mapping algorithm based on adaptive differential evolution for remote sensing imagery

Abstract

In this paper, a sub-pixel mapping algorithm based on differential evolution is proposed, namely adaptive differential evolution sub-pixel mapping algorithm (ADESM). In ADESM, the sub-pixel mapping problem becomes one of assigning land cover classes to the sub-pixels while maximizing the spatial dependence index (SDI). In the proposed ADESM algorithm, individuals are represented as a discrete sub-pixel mapping solution by discrete encoding strategy. These individuals are improved by enhanced evolution operators, e.g., mutation, crossover, repair, exchange, insertion, and an effective local search to generate new candidate solutions. Furthermore, ADESM may adaptively obtain the optimal sub-pixel mapping result without user-defined parameters by adaptive parameter-setting strategy. The proposed method was tested using the synthetic real imagery. Experimental results demonstrate that the proposed approach outperform traditional sub-pixel mapping algorithms, and hence provide an effective option for sub-pixel mapping of remote sensing imagery.