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Gradient Magnitude Based Normalised Convolution

Al-Kabbany, Ahmad, Coleman, SA and Kerr, D (2015) Gradient Magnitude Based Normalised Convolution. In: Irish Machine Vision and Image Processing Conference 2015, Trinity College, Dublin, Ireland .. Irish Pattern Recognition & Classification Society. 7 pp. [Conference contribution]

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URL: http://hdl.handle.net/2262/74714

Abstract

Although image data can often be sparse for a variety of different reasons, standard image processing techniques require the use of complete image data. Therefore sparse image data must undergo reconstruction to yield complete images prior to any subsequent processing. Highly accurate image reconstruction techniques tend to be expensive to implement whilst simpler techniques, such as image interpolation, are usually not adequate to support subsequent reliable image processing. A common approach to image reconstruction is normalised convolution; we present a modified approach to normalised convolution which is based on the sparse image content and we demonstrate that accurate reconstruction is achieved yielding better image processing results than the current standard normalised convolution.

Item Type:Conference contribution (Paper)
Keywords:Image reconstruction, Normalised convolution
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:32552
Deposited By: Dr Dermot Kerr
Deposited On:05 Nov 2015 09:33
Last Modified:05 Nov 2015 09:33

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