Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
Firefly Algorithm for Continuous Constrained Optimization Tasks
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Honey Bee Mating Optimization Vector Quantization Scheme in Image Compression
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
Firefly algorithms for multimodal optimization
SAGA'09 Proceedings of the 5th international conference on Stochastic algorithms: foundations and applications
Image compression method using improved PSO vector quantization
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
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The vector quantization (VQ) was a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. This paper proposed a new method based on the firefly algorithm to construct the codebook of vector quantization. The proposed method uses LBG method as the initial of firefly algorithm to develop the VQ algorithm. This method is called FF-LBG algorithm. The FF-LBG algorithm is compared with the other three methods that are LBG, PSO-LBG and HBMO-LBG algorithms. Experimental results showed that the computation of this proposed FF-LBG algorithm is faster than the PSO-LBG, and the HBMO-LBG algorithms. Furthermore, the reconstructured images get higher quality than those generated from the LBG and PSO-LBG algorithms, but there are not significantly different to the HBMO-LBG algorithm.