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2002, 7

A. Bounoua, S. M. A. Wady, M. F. Belbachir

A comparative survey for an adaptive FIR filter design in image compression by wavelets decomposition

language: English

received 24.04.2002, published 04.07.2002

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In this paper, adaptive filtering, wavelets, and lossy image compression are considered. Performances of the subband adaptive digital filter are discussed. We propose a transform coding method in which the low pass filters in the wavelets decomposition tree are time-varying. The idea is to decompose a digital image using an adaptive FIR (Finite Impulse Response) filter in each low frequency subband and compare it with an invariant filter of Daubechies. We employ a framework that includes the main comparison parameters. It is clearly shown here that it provides better performances than invariant filters in most applications. This work consists of applying an adaptive FIR filter by the ADFFLS (Adaptive Digital Filter with Fast Least Square) algorithm to digital images. The filter performances on the different stages of the data image compression chain are then valued and compared with an invariant and biorthogonal filter of Daubechies. This is done studying of the main parameters, namely the covariance matrix, the subband coding gain, the concentration of energy in the low frequency subband, the signal to noise ratio, the correlation, the bit allocation, and the compression ratio. This study resides in the meticulous choice of comparison parameters, and the different stages of comparison. Results show that the PSNR (Pic Signal Noise Ratio), the correlation between original and reconstructed images, and the compression ratio are better with the adaptive filter for different lengths, quantifiers, and quantification levels.

16 pages, 11 figures

Сitation: A. Bounoua, S. M. A. Wady, M. F. Belbachir. A comparative survey for an adaptive FIR filter design in image compression by wavelets decomposition. Electronic Journal “Technical Acoustics”,, 2002, 7.


[1] STRANG G., NGUYEN T. Wavelets and filter banks. MA: Wellesley-Cambridge Press, 1996.
[2] BOITE R., LEICH H. Les filtres numeriques: Analyse et synthese des filtres unidimensionnels. MASSON, Paris, 1990.
[3] RAMCHANDRAN K., VITERLI M. Best wavelet packet bases in a rate-distortion sense. IEEE Trans. image processing, Vol. 2, N°2, pp. 162-175, 1995.
[4] RUSHANAN J. J., AWIC V. "AdaptiveWIC"; for MTR-97B0000041. The MITRE Corporation, Bedford, MA, 1997.
[5] MIMOUN H., CIAZYNSKI M., BELLANGER M. Un logiciel d'aide a la conception des filtres adaptatifs sur PC. Traitement du signal, Vol. 7, N°6, 1990.
[6] BELLANGER M. Analyse des signaux et filtrage numerique adaptatif. MASSON, Paris, 1989.
[7] WADY S. M. A. Compression des images numeriques par decomposition en ondelettes adaptatives: Conception des filtres RIF adaptatifs. Memoire de Magister, Universite de Sidi bel abbes, Algerie, 2000.
[8] BOUNOUA A., GHAZ A. Etude comparative des filtres de decomposition M-bandes et ondelettes dans le codage des images numeriques. Seminaire sur l'Image et la Transmission (SIT'99), pp. 135-139, November 30th and December 1st 1999, Alger (Algeria).
[9] DAUBECHIES I. Ten lectures on wavelets. Society for Industrial and Applied Mathematics, Philadelphia, Pensylvania, 1992.
[10] PERDRIEAU L. Subband adaptive filtering by lattice structures: applyed to image compression. These, Universite de Rennes I, France, 1994.
[11] HOHENADEL M. Contribution in subbands and wavelet transform. These, Universite de Rennes I, France, 1994.
[12] GUILOIRE A., VITERLI M. Adaptive filtering in subband with critical sampling: Analysis, experiments and application to acoustic echo cancellation. IEEE Trans. Signal processing, Vol. 40, N°8, pp. 1862-1875, Aug. 1992.
[13] KUNT M. EAO: Atelier de Traitement Numerique des Signaux. Presses Polytechniques Romandes, Lausanne, Suisse, 1984.
[14] BELLANGER M. Analyse des signaux et filtrage adaptatif. MASSON, Paris, 1988.


Abdennacer Bounoua was born in Algeria. He received the dipl.El.-Ing. degree from the University of Science, and Technology of Oran (USTO, Algeria); the Master degree; and the Doctorat d'Etat from the University of Sidi Bel Abbes (Algeria), respectively in 1982, 1993 and 2002. Since 1985, he is a teaching member and involved in research on Digital Image Processing and Telecommunications, at the Department of Electronics, University of Sidi Bel-Abbes, Algeria.
E-mail: nbounoua(at)


Sanaa Mohamed Atta Wady was born in Algeria. She received the dipl.El.-Ing. degree and the Master degree from the University of Sidi Bel Abbes, Algeria, respectively in 1997 and 2000. Since 1997 to 2000, she is involved in research on digital image processing, at the department of electronics, University of Sidi Bel Abbes, Algeria, and since University of Saida, Algeria.


Bel Bachir Mohamed Faouzi was born in Oran, Algeria. He received the Dipl.El.-Ing. degree, the Master degree, and the these d'etat from the University of Science and Technology of Oran USTO (ORAN, Algeria) respectively in 1976, 1984 and 1991. Since 1981, he is at the Dept of Electronics of USTO. He is currently interested by the filter design and the image processing.