@inproceedings{df281da307ee49bfb5cbfeec2f4c74c3,
title = "Shift-variant image deblurring for machine vision: One-dimensional blur",
abstract = "Image deblurring is an important preprocessing step in the inspection and measurement applications of machine vision systems. A computational algorithm and analysis are presented for a new approach to one-dimensional shift-variant image deblurring. The new approach is based on a new mathematical transform that restates the traditional shift-variant image blurring model in a completely local but exactly equivalent form. The new approach is computationally noniterative, efficient, and permits very fine-grain parallel implementation. The theory of the new approach for onedimensional shift-variant deblurring is presented. Further, its advantages in comparison with related approaches, and experimental results are presented.",
keywords = "Deblurring, Deconvolution, Image Restoration, Integral Equation, Shift-Variant Blur",
author = "Muralidhara Subbarao and Kang, \{Youn Sik\} and Xue Tu",
year = "2009",
doi = "10.1117/12.825663",
language = "English",
isbn = "9780819477224",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Optical Inspection and Metrology for Non-Optics Industries",
note = "Optical Inspection and Metrology for Non-Optics Industries ; Conference date: 03-08-2009 Through 04-08-2009",
}