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Full-Text Articles in Physical Sciences and Mathematics
Coding Gain And Spatial Localisation Properties Of Discrete Wavelet Transform Filters For Image Coding, J Andrew, P Ogunbona, F Paoloni
Coding Gain And Spatial Localisation Properties Of Discrete Wavelet Transform Filters For Image Coding, J Andrew, P Ogunbona, F Paoloni
Professor Philip Ogunbona
The authors consider coding gain and spatial localisation properties of DWT filters for still image compression. Using a JPEG type quantisation and encoding method several images are compressed using a DWT implemented using various two-band subband filter sets. It is concluded that a relatively high coding gain (relative to a highly correlated source) is necessary, but not sufficient, for good image coding performance. Further, it is observed that low spatial width filters are desirable, particularly in regard to reduced ringing distortion. In terms of the tradeoff between coding gain and spatial localisation, and in terms of actual coding performance, it …
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Professor Philip Ogunbona
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
Securing Wavelet Compression With Random Permutations, Takeyuki Uehara, Reihaneh Safavi-Naini, Philip Ogunbona
Securing Wavelet Compression With Random Permutations, Takeyuki Uehara, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Wavelet compression for digital images achieves very high compression with reasonably high image quality and so is widely used in various applications. Adding security to compression algorithms has been proposed in a number of compression systems with the aim reducing the overall cost of compression and encryption. In this paper we propose a combined compression and encryption system based on wavelet transform and examine its security. Our results show that with a relatively small added cost varying degrees of security can be obtained while maintaining the performance of the compression system.
New Wavelet Based Art Network For Texture Classification, Jiazhao Wang, Golshah Naghdy, Philip O. Ogunbona
New Wavelet Based Art Network For Texture Classification, Jiazhao Wang, Golshah Naghdy, Philip O. Ogunbona
Professor Philip Ogunbona
A new method for texture classification is proposed. It is composed of two processing stages, namely, a low level evolutionary feature extraction based on Gabor wavelets and a high level neural network based pattern recognition. This resembles the process involved in the human visual system. Gabor wavelets are exploited as the feature extractor. A neural network, Fuzzy Adaptive Resonance Theory (Fuzzy ART), acts as the high level decision making and recognition system. Some modifications to the Fuzzy ART make it capable of simulating the post-natal and evolutionary development of the human visual system. The proposed system has been evaluated using …