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Comparison of Restoration Quality on Square and Hexagonal Grids using Normalized Convolution
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
2012 (English)In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR), 2012Conference paper, Published paper (Refereed)
Abstract [en]

Normalized convolution can be used to restore information that has been lost from an image, such as dead pixels, using the remaining information, and ignoring the incorrect pixels. It is known that the representation quality of an image consisting of a given number of pixels depends on how these pixels are distributed. In this paper, we investigate whether the ability to restore information using normalized convolution is affected by the sampling grid of the image. We compare square and hexagonal grids, and find that, in general, more pixels can be restored in hexagonal grids.

Place, publisher, year, edition, pages
2012.
National Category
Discrete Mathematics Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-188518OAI: oai:DiVA.org:uu-188518DiVA, id: diva2:578089
Conference
ICPR 2012
Available from: 2012-12-17 Created: 2012-12-17 Last updated: 2022-01-28

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Strand, Robin

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Linner, ElisabethStrand, Robin
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Division of Visual Information and InteractionComputerized Image Analysis and Human-Computer Interaction
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