An efficient cuckoo search algorithm based multilevel thresholding for segmentation of satellite images using different objective functions
作者：
Highlights：
• This paper proposes a computationally efficient optimization algorithm for segmenting colour satellite images.
• CS algorithm incorporating Mantegna’s and McCulloch’s method for modeling levy flight is presented.
• PSO, DPSO, ABC and CS algorithms are compared with the proposed algorithm.
• All these optimization algorithms are exploited using three different objective functions.
• Performance assessment metrics demonstrated the improvement in the efficiency of the proposed algorithm.
摘要
•This paper proposes a computationally efficient optimization algorithm for segmenting colour satellite images.•CS algorithm incorporating Mantegna’s and McCulloch’s method for modeling levy flight is presented.•PSO, DPSO, ABC and CS algorithms are compared with the proposed algorithm.•All these optimization algorithms are exploited using three different objective functions.•Performance assessment metrics demonstrated the improvement in the efficiency of the proposed algorithm.
论文关键词：Thresholding,Segmentation,Otsu’s between-class variance,Kapur ’s entropy,Tsallis entropy,Meta-heuristic algorithms,Mantegna’s method,McCulloch’s method
论文评审过程：Received 4 December 2015, Revised 20 March 2016, Accepted 21 March 2016, Available online 9 April 2016, Version of Record 27 April 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.03.032
