Faxed image restoration using Kalman filtering

Myoung Young Yoon, Seong Whan Lee, Ju Sung Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

We present a new scheme for the restoration of faxed images degraded by both salient noise and additive white noise. We consider two fundamental aspects of faxed image restoration: Modeling and the restoration algorithm. First, a model of a faxed image is presented. The model is based on an autoregressive Gauss-Markov random field and includes vertical and horizontal overlap effects. In particular, we concentrate on the nonsymmetric half plane causality. Second, the restoration of faxed images degraded by salient noise and additive white noise is considered by 2D Kalman filtering which provides an efficient recursive procedure. In order to illustrate the effectiveness of the proposed scheme, we present experimental results on the restoration of a faxed image.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995
PublisherIEEE Computer Society
Pages677-680
Number of pages4
ISBN (Electronic)0818671289
DOIs
Publication statusPublished - 1995 Jan 1
Event3rd International Conference on Document Analysis and Recognition, ICDAR 1995 - Montreal, Canada
Duration: 1995 Aug 141995 Aug 16

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2
ISSN (Print)1520-5363

Conference

Conference3rd International Conference on Document Analysis and Recognition, ICDAR 1995
CountryCanada
CityMontreal
Period95/8/1495/8/16

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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    Yoon, M. Y., Lee, S. W., & Kim, J. S. (1995). Faxed image restoration using Kalman filtering. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995 (pp. 677-680). [601987] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/ICDAR.1995.601987