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Physical Sciences and Mathematics Commons

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Selected Works

Professor Philip Ogunbona

Analysis

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Full-Text Articles in Physical Sciences and Mathematics

Texture Analysis Using Gabor Wavelets, Golshah Naghdy, Jianli Wang, Philip Ogunbona Sep 2012

Texture Analysis Using Gabor Wavelets, Golshah Naghdy, Jianli Wang, Philip Ogunbona

Professor Philip Ogunbona

Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symmetric or odd-symmetric Gabor filters. Computational models employed in the analysis of textures have been motivated by two-dimensional Gabor functions arranged in a multi-channel architecture. More recently wavelets have emerged as a powerful tool for non-stationary signal analysis capable of encoding scale-space information efficiently. A multi-resolution implementation in the form of a dyadic decomposition of the signal of interest has been popularized by many researchers. In this paper, Gabor wavelet configured in a 'rosette' fashion is used as a multi-channel filter-bank feature extractor for …


Signal Analysis Using A Multiresolution Form Of The Singular Value Decomposition, Ramakrishna Kakarala, Philip Ogunbona Sep 2012

Signal Analysis Using A Multiresolution Form Of The Singular Value Decomposition, Ramakrishna Kakarala, Philip Ogunbona

Professor Philip Ogunbona

This paper proposes a multiresolution form of the singular value decomposition (SVD) and shows how it may be used for signal analysis and approximation. It is well-known that the SVD has optimal decorrelation and subrank approximation properties. The multiresolution form of SVD proposed here retains those properties, and moreover, has linear computational complexity. By using the multiresolution SVD, the following important characteristics of a signal may be measured, at each of several levels of resolution: isotropy, sphericity of principal components, self-similarity under scaling, and resolution of mean-squared error into meaningful components. Theoretical calculations are provided for simple statistical models to …