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Optimized color space for image compression based on DCT and Bat algorithm

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Abstract

This paper develops an efficient color image compression method based on the DCT and a new color base. Digital color images are commonly represented in RGB space. Generally, it is noted that a strong correlation exists between the three planes R, G, and B of a color image. The reduction of this correlation certainly offers an advantage in the compression of RGB images. In this context, there is an infinite number of possible spaces to represent the RGB image. The main contributions of this paper are summarized in two main points. First, we design an optimized color space B1B2B3 using the Bat algorithm (BA) to pass from the RGB space to space more appropriate for each image. This space is produced by maximizing the energy of the image in the plane B1 more than in B2 and B3. Second, we produce optimized thresholds appropriate to each plane of the converted image. The Bat algorithm optimizes the cost function to compute thresholds to partially reduce the number of the less significant DCT coefficients that correspond to the lower quantity of energy. The reported results against those of recent methods prove that the proposed method presents high performances in terms of peak signal to noise ratio (PSNR) on the commonly used test color images as well as the test medical images in literature.

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Authors and Affiliations

  1. Energy Systems Modeling Laboratory, University of Biskra, Biskra, Algeria

    Djamel Eddine Touil

  2. LESIA Laboratory, Department of Electrical Engineering, University of Biskra, Biskra, Algeria

    Nadjiba Terki

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  1. Djamel Eddine Touil
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  2. Nadjiba Terki
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Correspondence to Djamel Eddine Touil.

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Touil, D.E., Terki, N. Optimized color space for image compression based on DCT and Bat algorithm. Multimed Tools Appl 80, 9547–9567 (2021). https://doi.org/10.1007/s11042-020-09754-0

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  • DOI: https://doi.org/10.1007/s11042-020-09754-0

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