Affiliations: [a] Ecole Nationale Polytechnique, Electronic Department, El Harrach, Algeria
| [b]
Research Center in Industrial Technologies CRTI, Cheraga, Algiers, Algeria
| [c]
Wayne State University, Department of Biomedical Engineering, Detroit, MI, USA
Correspondence:
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Corresponding author: Mekhalfa Faiza is with Signal & communications Lab, Department of Electronic, Ecole Nationale Polytechnique, 10 Avenue Hassan Badi BP 182, El Harrach 16200, Algeria. Tel/Fax: +213 21 52 29 73; and with Research Center in Industrial Technologies CRTI, P.O. Box 64, Cheraga 16014, Algiers, Algeria., Tel/Fax: +213 21 34 20 19. E-mail: [email protected].
Abstract: In this work a lossless wavelet-fractal image coder is proposed. The process starts by compressing and decompressing the original image using wavelet transformation and fractal coding algorithm. The decompressed image is removed from the original one to obtain a residual image which is coded by using Huffman algorithm. Simulation results show that with the proposed scheme, we achieve an infinite peak signal to noise ratio (PSNR) with higher compression ratio compared to typical lossless method. Moreover, the use of wavelet transform speeds up the fractal compression algorithm by reducing the size of the domain pool. The compression results of several welding radiographic images using the proposed scheme are evaluated quantitatively and compared with the results of Huffman coding algorithm.
