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Multi-resolution mean-shift algorithm for vector quantization

Conference Paper


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Abstract


  • The generation of stratified codebooks, providing a subset of vectors at different scale levels, has become necessary with the emergence of embedded coder/decoder for scalable image and video formats. We propose an approach based on mean-shift, invoking the multi-resolution framework to generate codebook vectors. Applied to the entire image, mean-shift is slow because it requires each sample to converge to a mode of the distribution. The procedure can be sped up with three simple assumptions: kernel truncation, code attraction and trajectory attraction. Here we propose to apply the mean-shift algorithm to the four image subbands generated by a DWT, namely the LL, LH, HL and HH subbands. It can be concluded from experimental results that the proposed MR-MS achieves similar PSNR to the LBG algorithm but outperforms it in terms of computation time.

Publication Date


  • 2010

Citation


  • Bouttefroy, P., Bouzerdoum, A., Beghdadi, A. & Phung, S. Lam. (2010). Multi-resolution mean-shift algorithm for vector quantization. Data Compression Conference (pp. 523-523). USA: IEEE.

Scopus Eid


  • 2-s2.0-77952688120

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1845&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/832

Has Global Citation Frequency


Start Page


  • 523

End Page


  • 523

Place Of Publication


  • USA

Abstract


  • The generation of stratified codebooks, providing a subset of vectors at different scale levels, has become necessary with the emergence of embedded coder/decoder for scalable image and video formats. We propose an approach based on mean-shift, invoking the multi-resolution framework to generate codebook vectors. Applied to the entire image, mean-shift is slow because it requires each sample to converge to a mode of the distribution. The procedure can be sped up with three simple assumptions: kernel truncation, code attraction and trajectory attraction. Here we propose to apply the mean-shift algorithm to the four image subbands generated by a DWT, namely the LL, LH, HL and HH subbands. It can be concluded from experimental results that the proposed MR-MS achieves similar PSNR to the LBG algorithm but outperforms it in terms of computation time.

Publication Date


  • 2010

Citation


  • Bouttefroy, P., Bouzerdoum, A., Beghdadi, A. & Phung, S. Lam. (2010). Multi-resolution mean-shift algorithm for vector quantization. Data Compression Conference (pp. 523-523). USA: IEEE.

Scopus Eid


  • 2-s2.0-77952688120

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1845&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/832

Has Global Citation Frequency


Start Page


  • 523

End Page


  • 523

Place Of Publication


  • USA