An efficient algorithm for gray level image enhancement using cuckoo search

Authors:
Sanjay Agrawal;Rutuparna Panda
Affiliations:
Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla, Odisha, India;Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla, Odisha, India
Venue:
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Year:
2012

Citing 5
Cited 0

Digital image processing (2nd ed.)

Digital image processing (2nd ed.)
Genetic algorithms for optimal image enhancement

Pattern Recognition Letters
Evolutionary image enhancement with user behavior modeling

ACM SIGAPP Applied Computing Review
Gray-scale image enhancement as an automatic process driven by evolution

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
FSIM: A Feature Similarity Index for Image Quality Assessment

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an efficient algorithm for gray level image enhancement using Cuckoo search (CS). The results are compared with Particle Swarm Optimization (PSO). The basic idea is to treat image enhancement as an optimization problem and then solve it using CS. It is observed that the proposed method provides better results than existing techniques.