A Novel Adaptive Cuckoo Search Algorithm for Contrast Enhancement of Satellite Images

Shilpa Suresh, Shyam Lal, Chintala Sudhakar Reddy, Mustafa Servet Kiran

Research output: Contribution to journalArticlepeer-review

51 Citations (Scopus)


Owing to the increased demand for satellite images for various practical applications, the use of proper enhancement methods are inevitable. Visual enhancement of such images mainly focuses on improving the contrast of the scene procured, conserving its naturalness with minimum image artifacts. Last one decade traced an extensive use of metaheuristic approaches for automatic image enhancement processes. In this paper, a robust and novel adaptive Cuckoo search based Enhancement algorithm is proposed for the enhancement of various satellite images. The proposed algorithm includes a chaotic initialization phase, an adaptive Levy flight strategy and a mutative randomization phase. Performance evaluation is done by quantitative and qualitative results comparison of the proposed algorithm with other state-of-the-art metaheuristic algorithms. Box-and-whisker plots are also included for evaluating the stability and convergence capability of all the algorithms tested. Test results substantiate the efficiency and robustness of the proposed algorithm in enhancing a wide range of satellite images.

Original languageEnglish
Article number7939253
Pages (from-to)3665-3676
Number of pages12
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Issue number8
Publication statusPublished - 08-2017

All Science Journal Classification (ASJC) codes

  • Computers in Earth Sciences
  • Atmospheric Science


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