Image Compression Using Subband Wavelet Decomposition and DCT-based Quantization

Mahmoud Addouche (1) , Fatma Zohra Nacer (2) , Réda Yahiaoui (1)

1 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)
2 ECE - Ecole Centrale d'Electronique

The aim of this work is to evaluate the performance of an image compression system based on wavelet-based subband decomposition. The compression method used in this paper differs from the classical procedure in the direction where the scalar quantization of the coarse scale approximation sub-image is replaced by a discrete cosine transform (DCT) based quantization. The images were decomposed using wavelet filters into a set of subbands with different resolutions corresponding to different frequency bands. The resulting high frequency subbands were vector quantized according to the magnitude of their variances. The coarse scale approximation sub-image is quantized using scalar quantization and then using DCT base quantization to show the benefit of this new optional method in term of CPU computationa1 cost vs restitution quality.

Mots clés: Wavelets; image compression; embedded systems

Domaines: Autre; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Mahmoud Addouche, Fatma Zohra Nacer, Réda Yahiaoui. Image Compression Using Subband Wavelet Decomposition and DCT-based Quantization. World Scientific and Engineering Academy and Society transactions on signal processing, 2006, 2 (4), pp.518-524. ⟨hal-00080377⟩