A novel color image multilevel thresholding based segmentation using nature inspired optimization algorithms

作者：

Highlights：

• This paper introduces the comparative performance of different objective functions (Kapur's & Otsu).

• Evolutionary algorithm based multilevel thresholding for a color satellite image has been presented.

• DE, WDO, PSO and CS algorithms are exploited with Kapur's and Otsu method.

• CS based Kapur's entropy was found to be more accurate for colored satellite image segmentation.

摘要

• This paper introduces the comparative performance of different objective functions (Kapur's & Otsu).• Evolutionary algorithm based multilevel thresholding for a color satellite image has been presented.• DE, WDO, PSO and CS algorithms are exploited with Kapur's and Otsu method.• CS based Kapur's entropy was found to be more accurate for colored satellite image segmentation.

论文关键词：Color image segmentation,Multilevel thresholding,Nature inspired optimization algorithms,Cuckoo search algorithm,Kapur's and Otsu method

论文评审过程：Received 27 December 2015, Revised 26 June 2016, Accepted 26 June 2016, Available online 27 June 2016, Version of Record 6 July 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.06.044