Abstract
The principal objective of enhancement is to improve the contrast and detail an image so, that the result is more suitable than the original image for a specific application. The enhancement process is a non-linear optimization problem with several constraints. In this paper, an adaptive local enhancement algorithm based on Firefly Algorithm (FA) is proposed. FA represents a new approach for optimization. The FA is used to search the optimal parameters for the best enhancement. In the proposed method, the evaluation criterion is defined by edge numbers, edge intensity and the entropy. The proposed method is demonstrated and compared with Linear Contrast Stretching (LCS), Histogram Equalization (HE), Genetic Algorithm based image Enhancement (GAIE), and the Particle Swarm Optimization based image enhancement (PSOIE) methods. Experimental results presented that proposed technique offers better performance.
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Hassanzadeh, T., Vojodi, H., Mahmoudi, F. (2011). Non-linear Grayscale Image Enhancement Based on Firefly Algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_21
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DOI: https://doi.org/10.1007/978-3-642-27242-4_21
Publisher Name: Springer, Berlin, Heidelberg
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