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Image Contrast Enhancement Using Hybrid Elitist Ant System, Elitism-Based Immigrants Genetic Algorithm and Simulated Annealing

  • Rajeev Kumar
  • Anand Gupta
  • Apoorv Gupta
  • Aman Bansal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 703)

Abstract

Contrast enhancement is a technique which is used to expand the range of intensities within the image to make its features more distinct and easily perceptible to the human eye. It has found many applications ranging from medical to satellite imagery where the primary aim is to find hidden or minute details within an image. Through literary research, the authors have realised that the existing approaches lag behind in enhancing the contrast of an image. Hence in the present paper, an improved contrast enhancement technique is proposed which is based on the hybrid combination of nature-based metaheuristics: Elitist Ant System (EAS), Elitism-based Genetic Algorithm (EIGA) and Simulated Annealing (SA). EAS and EIGA work together to search globally for the optimum solution which is then refined by SA locally. Through experiment, it is observed that the proposed algorithm is efficiently improving the contrast of an image when compared with existing algorithms.

Keywords

Contrast enhancement Elitist ant system Elitism-based immigrants genetic algorithm Simulated annealing 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Rajeev Kumar
    • 1
  • Anand Gupta
    • 1
  • Apoorv Gupta
    • 2
  • Aman Bansal
    • 2
  1. 1.Department of Computer EngineeringNSIT, University of DelhiNew DelhiIndia
  2. 2.Department of Information TechnologyNSIT, University of DelhiNew DelhiIndia

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