Vector Quantization Using a Modified Firefly Algorithm for Image Compression

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Amouei Sorayya; Mirzaie Kamal

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Journal Paper

Paper Information

Journal: TABRIZ JOURNAL OF ELECTRICAL ENGINEERING Year:2019 | Volume:49 | Issue:2 (88) Page(s): 693-707

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Information Journal Paper

Title

Vector Quantization Using a Modified Firefly Algorithm for Image Compression

Author(s)

Amouei Sorayya | Mirzaie Kamal | Issue Writer Certificate

Keywords

Image CompressionQ3

Vector QuantizationQ2

Swarm IntelligenceQ2

Firefly AlgorithmQ1

Abstract

Vector Quantization (VQ) is the powerful technique in Image Compression. Generating a good codebook is an important part of VQ. There are various algorithms in order to generate an optimal codebook. Recently, Swarm Intelligence (SI) algorithms were adapted to obtain the near-global optimal codebook of VQ. In this paper, we proposed a new method based on a modified Firefly Algorithm (MFA) to construct the codebook of VQ. The proposed method merged genetic crossover operator with FA to develop the VQ. This method is called MFA model. Experimental results indicate that the reconstructed images generated by the proposed model is get higher quality than FA and it’ s about one percent, but it is no significant superiority to the PSO algorithm. Furthermore, MFA is slower than FA.

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APA: Copy

Amouei, Sorayya, & Mirzaie, Kamal. (2019). Vector Quantization Using a Modified Firefly Algorithm for Image Compression. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 49(2 (88) ), 693-707. SID. https://sid.ir/paper/256480/en

Vancouver: Copy

Amouei Sorayya, Mirzaie Kamal. Vector Quantization Using a Modified Firefly Algorithm for Image Compression. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2019;49(2 (88) ):693-707. Available from: https://sid.ir/paper/256480/en

IEEE: Copy

Sorayya Amouei, and Kamal Mirzaie, “Vector Quantization Using a Modified Firefly Algorithm for Image Compression,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 49, no. 2 (88) , pp. 693–707, 2019, [Online]. Available: https://sid.ir/paper/256480/en

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