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An Improved Cuckoo Search based Optimal Ranged Brightness Preserved Histogram Equalization and Contrast Stretching Method

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  • Krishna Gopal Dhal

    (Department of 4-year BTech Course, University of Calcutta, Kolkata, India)

  • Md. Iqbal Quraishi

    (Department of Information Technology, Kalyani Government Engineering College, Kalyani, India)

  • Sanjoy Das

    (Department of Engineering and Technological Studies, University of Kalyani, Kalyani, India)

Abstract

This paper is organized into two main parts. In the first part, two methods have been discussed to preserve the original brightness of the image which are Parameterized transformation function and a novel variant of modified Histogram Equalization (HE) method. In this study both methods have been formulated as optimization problems to increase the efficiency of the corresponding methods within reasonable time. In the second part, a novel modified version of Cuckoo Search (CS) algorithm has been devised by using chaotic sequence, population diversity information etc to solve those formulated optimization problems. A new Co-occurrence matrix's features based objective function is also devised to preserve the original brightness. Peak-signal to noise ratio (PSNR) acts as objective function to find optimal range of enhanced images. Experimental results prove the supremacy of the proposed CS over traditional CS algorithm.

Suggested Citation

  • Krishna Gopal Dhal & Md. Iqbal Quraishi & Sanjoy Das, 2017. "An Improved Cuckoo Search based Optimal Ranged Brightness Preserved Histogram Equalization and Contrast Stretching Method," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 8(1), pages 1-29, January.
  • Handle: RePEc:igg:jsir00:v:8:y:2017:i:1:p:1-29
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