Image De-Quantization Using Plate Bending Model
Algorithms. 2018;11(8):110 DOI 10.3390/a11080110
LCC Subject Category: Technology: Technology (General): Industrial engineering. Management engineering | Science: Mathematics: Instruments and machines: Electronic computers. Computer science
Country of publisher: Switzerland
Language of fulltext: English
Full-text formats available: PDF, HTML, XML
AUTHORS
David Völgyes
(Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway)
Anne Catrine Trægde Martinsen
(Department of Physics, University of Oslo, 0316 Oslo, Norway)
Arne Stray-Pedersen
(Department of Forensic Sciences, Oslo University Hospital, 0424 Oslo, Norway)
Dag Waaler
(Department of Health Sciences in Gjøvik, Norwegian University of Science and Technology, 2803 Gjøvik, Norway)
Marius Pedersen
(Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway)
EDITORIAL INFORMATION
Time From Submission to Publication: 11 weeks
Abstract | Full Text
Discretized image signals might have a lower dynamic range than the display. Because of this, false contours might appear when the image has the same pixel value for a larger region and the distance between pixel levels reaches the noticeable difference threshold. There have been several methods aimed at approximating the high bit depth of the original signal. Our method models a region with a bended plate model, which leads to the biharmonic equation. This method addresses several new aspects: the reconstruction of non-continuous regions when foreground objects split the area into separate regions; the incorporation of confidence about pixel levels, making the model tunable; and the method gives a physics-inspired way to handle local maximal/minimal regions. The solution of the biharmonic equation yields a smooth high-order signal approximation and handles the local maxima/minima problems.
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