Adaptive Wavelet Transform for Image Compression via Directional Quincunx Lifting

Adaptive Wavelet Transform for Image Compression via Directional Quincunx Lifting

We propose a novel adaptive wavelet transform that exploits local image properties for image compression. It combines wavelet filters adaptive to edge orientations with quincunx subsampling to form a 2-D nonseparable transform through lifting. Filter selections are efficiently represented. Significa...

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Bibliographische Detailangaben
Hauptverfasser: Chuo-Ling Chang, Maleki, A., Girod, B.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Adaptive filters
Decoding
Discrete transforms
Discrete wavelet transforms
Filtering
Helium
Image coding
Information systems
Quantization
Wavelet transforms
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Beschreibung
Zusammenfassung:We propose a novel adaptive wavelet transform that exploits local image properties for image compression. It combines wavelet filters adaptive to edge orientations with quincunx subsampling to form a 2-D nonseparable transform through lifting. Filter selections are efficiently represented. Significant improvement on both subjective and objective quality over the conventional separable transform is observed. In addition, unlike previous adaptive transforms, the symmetry in quincunx subsampling enables even quality for image features along different directions and the compression performance is insensitive to image orientation
DOI:10.1109/MMSP.2005.248564