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Sub-pixel mapping of remote-sensing imagery based on chaotic quantum bee colony algorithm

The spatial dependence theory is basic theory of sub-pixel mapping SPM. A sub-pixel/pixel spatial attraction model SPSAM can realise the spatial dependence theory directly, however, the results created by SPSAM are noisy and the accuracy is limited. In this paper, a method based on chaotic quantum bee colony algorithm CQBCA is proposed to realise SPM. The proposed method contained two main steps: SPSAM is used to generate the initial result, and CQBCA as the post-process method to improve the SPSAM. Experimental results reveal that the proposed method can provide higher accuracy and reduce the noise in the results created by SPSAM. Furthermore, when compared with the particle swarm optimisation-based sub-pixel mapping, the proposed method often yields better accuracy results.