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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Index Factorised Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Factorised Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
No abstract provided.
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Professor Philip Ogunbona
A modified fuzzy adaptive resonance theory neural network (ART) is used as a classifier for a texture recognition system. The system consists of a wavelet based low level feature detector and a high level ART classifier. The performance improvement is measured in terms of identification accuracy and computational burden.
Index Compressed Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Compressed Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
This paper introduces an improved image adaptive vector quantisation technique - index compressed image adaptive vector quantisation (IC-IAVQ). Despite its advantage over the universal codebook VQ, basic image adaptive VQ (IAVQ) is still suboptimum; it neglects the correlation among block indices in the encoded image. The new technique, IC-IAVQ, overcomes this suboptimality through a pre-processing and lossless compression of block indices. Simulation results using several images show that IC-IAVQ outperforms IAVQ and entropy coded IAVQ, especially at low bit-rates by about 2dB on average.