Abstract
Given an image, there is no unique measure to quantitatively judge the quality of an image enhancement operator. It is also not clear which measure is to be used for the given image. The present work expresses the problem as a multi-objective optimization problem and a methodology has been proposed based on multi-objective genetic algorithm (MOGA). The methodology exploits the effectiveness of MOGA for searching global optimal solutions in selecting an appropriate image enhancement operator.
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Rosenfeld, A., Kak, A.C.: Digital picture processing. Academic Press, New York (1982)
Ekstrom, M.P.: Digital image processing techniques. Academic Press, New York (1984)
Kundu, M.K., Pal, S.K.: Automatic selection of object enhancement operator with quantitative justification based on fuzzy set theoretic measure. Pattern Recognition Letters 11, 811–829 (1990)
Pal, S.K., Bhandari, D., Kundu, M.K.: Genetic algorithms for optimal image enhancement. Pattern Recognition Letters 15, 261–271 (1994)
Vlachos, I.K., Sergiadis, G.D.: Parametric indices of fuzziness for automated image enhancement. Fuzzy Sets and Systems 157, 1126–1138 (2006)
Cheng, H.D., Li, J.: Fuzzy homogeneity and scale-space approach to color image segmentation. Pattern Recognition 36, 1545–1562 (2003)
Munteanu, C., Rosa, A.: Gray-scale image enhancement as an automatic process driven by evolution. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics 34(2), 1292–1298 (2004)
Srinivas, N., Deb, K.: Multiobjective function optimization using nondominated sorting genetic algorithms. Evolutionary Computation Journal 2(3), 221–248 (1995)
Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley, Chichester (2001)
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Bhandari, D., Murthy, C.A., Pal, S.K. (2009). Image Enhancement Using Multi-objective Genetic Algorithms. In: Chaudhury, S., Mitra, S., Murthy, C.A., Sastry, P.S., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2009. Lecture Notes in Computer Science, vol 5909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11164-8_50
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DOI: https://doi.org/10.1007/978-3-642-11164-8_50
Publisher Name: Springer, Berlin, Heidelberg
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