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Yang, Seungjoon
Signal Processing Lab (SPL)
Research Interests
  • Statistical signal processing, multi-rate systems, image/video processing, computer vision

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Modeling nonstationary lens blur using eigen blur kernels for restoration

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Title
Modeling nonstationary lens blur using eigen blur kernels for restoration
Author
Gwak, MoonsungYang, Seungjoon
Issue Date
2020-12
Publisher
OPTICAL SOC AMER
Citation
OPTICS EXPRESS, v.28, no.26, pp.405448
Abstract
Images acquired through a lens show nonstationary blur due to defocus and optical aberrations. This paper presents a method for accurately modeling nonstationary lens blur using eigen blur kernels obtained from samples of blur kernels through principal component analysis. Pixelwise variant nonstationary lens blur is expressed as a linear combination of stationary blur by eigen blur kernels. Operations that represent nonstationary blur can be implemented efficiently using the discrete Fourier transform. The proposed method provides a more accurate and efficient approach to modeling nonstationary blur compared with a widely used method called the efficient filter flow, which assumes stationarity within image regions. The proposed eigen blur kernel-based modeling is applied to total variation restoration of nonstationary lens blur. Accurate and efficient modeling of blur leads to improved restoration performance. The proposed method can be applied to model various nonstationary degradations of image acquisition processes, where degradation information is available only at some sparse pixel locations. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
URI
https://scholarworks.unist.ac.kr/handle/201301/49100
URL
https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-28-26-39501&id=444798
DOI
10.1364/OE.405448
ISSN
1094-4087
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