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Quality Preserved Color Image Compression Using Particle Swarm Optimization Algorithm

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Modelling and Implementation of Complex Systems (MISC 2020)


In this paper, we propose an efficient discrete wavelet transform-based compression method for color images. Generally, the strong correlation exists between the three planes R, G, and B of a color image, where the decrease of this correlation gives an improvement in the compression quality. The proposed method utilizes an efficient technique to reduce this correlation efficiently. In this regard, the main contribution is to design an optimized color space \(S_1S_2S_3\) using the PSO algorithm to represent the RGB image in a space more appropriate for performing the compression. The idea is to maximize the energy of the image in the plane \(S_1\) more than in \(S_2\) and \(S_3\). Moreover, we propose to optimize the thresholds appropriate for each plane of the converted image to partially reduce the number of the less important DWT coefficients that correspond to the lower quantity of energy. The obtained results facing those of state-of-the-art methods confirm that the proposed method shows clearly that the proposed method achieves high performances .

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Correspondence to Djamel Eddine Touil .

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Touil, D.E., Terki, N. (2021). Quality Preserved Color Image Compression Using Particle Swarm Optimization Algorithm. In: Chikhi, S., Amine, A., Chaoui, A., Saidouni, D., Kholladi, M. (eds) Modelling and Implementation of Complex Systems. MISC 2020. Lecture Notes in Networks and Systems, vol 156. Springer, Cham.

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  • Print ISBN: 978-3-030-58860-1

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