Efficient coding by neuro-fuzzy clustering in vector quantization of wavelet decomposed signals

Sunanda Mitra, Surya Pemmaraju

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

Multiresolution representation of wavelets in image decomposition and coding shows potential of developing an efficient image compression technique with minimum distortion when vector quantization (VQ) is used. This paper presents a multiresolution and adaptive approach to VQ codebook generation by employing a fuzzy distortion measure embedded in a self-organizing neural network ensuring fast convergence and minimum distortion. Multiresolution codebooks are generated for the wavelet decomposed images using neuro-fuzzy clustering algorithms resulting in significant improvement in the coding process. The signal transformation and vector quantization stages together yield, at least, 64:1 bit rate reduction with good visual quality and acceptable peak signal to noise ratio (PSNR) and mean square error (MSE). The performance of this new VQ coding technique has been compared to that of the well-known Linde, Buzo, and Gray (LBG) - VQ for a variety of image classes. In each case, the new VQ technique demonstrated superior ability for fast convergence with minimum distortion at similar bit rate reduction than the existing VQ techniques.

Original languageEnglish
Pages229-233
Number of pages5
StatePublished - 1996
EventProceedings of the 1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS - Berkeley, CA, USA
Duration: Jun 19 1996Jun 22 1996

Conference

ConferenceProceedings of the 1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS
CityBerkeley, CA, USA
Period06/19/9606/22/96

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    Mitra, S., & Pemmaraju, S. (1996). Efficient coding by neuro-fuzzy clustering in vector quantization of wavelet decomposed signals. 229-233. Paper presented at Proceedings of the 1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS, Berkeley, CA, USA, .