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Physical Sciences and Mathematics Commons

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Selected Works

Professor Philip Ogunbona

Vector

Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

Index-Compressed Vector Quantisation Based On Index Mapping, Jamshid Shanbehzadeh, Philip Ogunbona Sep 2012

Index-Compressed Vector Quantisation Based On Index Mapping, Jamshid Shanbehzadeh, Philip Ogunbona

Professor Philip Ogunbona

The authors introduce a novel coding technique which significantly improves the performance of the traditional vector quantisation (VQ) schemes at low bit rates. High interblock correlation in natural images results in a high probability that neighbouring image blocks are mapped to small subsets of the VQ codebook, which contains highly correlated codevectors. If, instead of the whole VQ codebook, a small subset is considered for the purpose of encoding neighbouring blocks, it is possible to improve the performance of traditional VQ schemes significantly. The performance improvement obtained with the new method is about 3dB on average when compared with traditional …


Channel-Optimized Vector Trellis Source Coding For The Awgn Channel, Philip Secker, Philip Ogunbona Sep 2012

Channel-Optimized Vector Trellis Source Coding For The Awgn Channel, Philip Secker, Philip Ogunbona

Professor Philip Ogunbona

A channel-optimised (joint source and channel) trellis source coder is designed for the AWGN channel. The optimum decoder is a non-linear function of the real channel information. The extension to 2D vector alphabets coupled with modifications to the signal space are found to improve performance. Favourable comparisons are made against a trellis source coder/TCM system.


New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona Sep 2012

New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona

Professor Philip Ogunbona

It is difficult to achieve a good low bit rate image compression performance with traditional block coding schemes such as transform coding and vector quantization, without regard for the human visual perception or signal dependency. These classical block coding schemes are based on minimizing the MSE at a certain rate. This procedure results in more bits being allocated to areas which may not be visually important and the resulting quantization noise manifests as a blocking artifact. Blocking artifacts are known to be psychologically more annoying than white noise when the human visual response is considered. While image adaptive vector quantization …