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Proceedings Paper

Blur kernel estimation with algebraic tomography technique and intensity profiles of object boundaries
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Paper Abstract

Motion blur caused by camera vibration is a common source of degradation in photographs. In this paper we study the problem of finding the point spread function (PSF) of a blurred image using the tomography technique. The PSF reconstruction result strongly depends on the particular tomography technique used. We present a tomography algorithm with regularization adapted specifically for this task. We use the algebraic reconstruction technique (ART algorithm) as the starting algorithm and introduce regularization. We use the conjugate gradient method for numerical implementation of the proposed approach. The algorithm is tested using a dataset which contains 9 kernels extracted from real photographs by the Adobe corporation where the point spread function is known. We also investigate influence of noise on the quality of image reconstruction and investigate how the number of projections influence the magnitude change of the reconstruction error.

Paper Details

Date Published: 13 April 2018
PDF: 7 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 1069626 (13 April 2018); doi: 10.1117/12.2310064
Show Author Affiliations
Anastasia Ingacheva, Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)
National Research Univ. Higher School of Economics (Russian Federation)
Marina Chukalina, Institute of Microelectronics Technology and High Purity Materials (Russian Federation)
Timur Khanipov, Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)
Dmitry Nikolaev, Institute for Information Transmission Problems (Kharkevich Institute) (Russian Federation)


Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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