Double deconvolution using a neural network

Chong Sze TONG

doi:10.1109/SIPNN.1994.344824

Double deconvolution using a neural network

Chong Sze TONG^*

^*Corresponding author for this work

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

The restoration of a blurred digital image usually requires accurate knowledge of the blurring process which, however, may not always be available. This paper describes a double iterative scheme for the simultaneous identification of the blurring and its removal by making use of the neural network paradigm and assumption of physical constraints on the blurring process.

Original language	English
Title of host publication	ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings
Publisher	IEEE
Pages	662-665
Number of pages	4
ISBN (Electronic)	078031865X, 9780780318656
DOIs	https://doi.org/10.1109/SIPNN.1994.344824
Publication status	Published - 1994
Event	1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994 - Hong Kong, Hong Kong Duration: 13 Apr 1994 → 16 Apr 1994

Publication series

Name	ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings

Conference

Conference	1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994
Country/Territory	Hong Kong
City	Hong Kong
Period	13/04/94 → 16/04/94

Scopus Subject Areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Signal Processing
Linguistics and Language

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10.1109/SIPNN.1994.344824

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@inproceedings{a5bcc5dd05b640f684be8165b37d190b,

title = "Double deconvolution using a neural network",

abstract = "The restoration of a blurred digital image usually requires accurate knowledge of the blurring process which, however, may not always be available. This paper describes a double iterative scheme for the simultaneous identification of the blurring and its removal by making use of the neural network paradigm and assumption of physical constraints on the blurring process.",

author = "TONG, {Chong Sze}",

note = "Publisher Copyright: {\textcopyright} 1994 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994 ; Conference date: 13-04-1994 Through 16-04-1994",

year = "1994",

doi = "10.1109/SIPNN.1994.344824",

language = "English",

series = "ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings",

publisher = "IEEE",

pages = "662--665",

booktitle = "ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings",

address = "United States",

}

TONG, CS 1994, Double deconvolution using a neural network. in ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings., 344824, ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings, IEEE, pp. 662-665, 1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994, Hong Kong, Hong Kong, 13/04/94. https://doi.org/10.1109/SIPNN.1994.344824

Double deconvolution using a neural network. / TONG, Chong Sze.
ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings. IEEE, 1994. p. 662-665 344824 (ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AB - The restoration of a blurred digital image usually requires accurate knowledge of the blurring process which, however, may not always be available. This paper describes a double iterative scheme for the simultaneous identification of the blurring and its removal by making use of the neural network paradigm and assumption of physical constraints on the blurring process.

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DO - 10.1109/SIPNN.1994.344824

M3 - Conference proceeding

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T3 - ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings

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BT - ISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings

PB - IEEE

T2 - 1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994

Y2 - 13 April 1994 through 16 April 1994

ER -

Double deconvolution using a neural network

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