Scanned images resolution improvement using neural networks
A novel method of improving the spatial resolution of scanned images, by means of neural networks, is presented in this paper. Images of different resolution, originating from scanner, successively train a neural network, which learns to improve resolution from 25 to 50 pixels-per-inch (ppi), then f...
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nemertes-10889-48402022-09-06T07:03:55Z Scanned images resolution improvement using neural networks Panagiotopoulou, Antigoni Anastassopoulos, Vassilis Παναγιωτοπούλου, Αντιγόνη Αναστασόπουλος, Βασίλειος Resolution improvement Neural network Scanner A novel method of improving the spatial resolution of scanned images, by means of neural networks, is presented in this paper. Images of different resolution, originating from scanner, successively train a neural network, which learns to improve resolution from 25 to 50 pixels-per-inch (ppi), then from 100 to 200 ppi and finally, from 50 to 100 ppi. Thus, the network is provided with consistent knowledge regarding the point spread function (PSF) of the scanner, whilst it gains the generalization ability to reconstruct finer resolution images unfamiliar to it. The novelty of the proposed image-resolution-enhancement technique lies in the successive training of the neural structure with images of increasing resolution. Comparisons with the image scanned at 400 ppi demonstrate the superiority of our method to conventional interpolation techniques. 2011-12-08T09:22:55Z 2011-12-08T09:22:55Z 2008 2011-12-08 Journal (paper) http://hdl.handle.net/10889/4840 en http://dx.doi.org/10.1007/s00521-007-0106-x application/pdf Neural Computing & Applications |
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UPatras |
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Nemertes |
language |
English |
topic |
Resolution improvement Neural network Scanner |
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Resolution improvement Neural network Scanner Panagiotopoulou, Antigoni Anastassopoulos, Vassilis Scanned images resolution improvement using neural networks |
description |
A novel method of improving the spatial resolution of scanned images, by means of neural networks, is presented in this paper. Images of different resolution, originating from scanner, successively train a neural network, which learns to improve resolution from 25 to 50 pixels-per-inch (ppi), then from 100 to 200 ppi and finally, from 50 to 100 ppi. Thus, the network is provided with consistent knowledge regarding the point spread function (PSF) of the scanner, whilst it gains the generalization ability to reconstruct finer resolution images unfamiliar to it. The novelty of the proposed image-resolution-enhancement technique lies in the successive training of the neural structure with images of increasing resolution. Comparisons with the image scanned at 400 ppi demonstrate the superiority of our method to conventional interpolation techniques. |
author2 |
Παναγιωτοπούλου, Αντιγόνη |
author_facet |
Παναγιωτοπούλου, Αντιγόνη Panagiotopoulou, Antigoni Anastassopoulos, Vassilis |
format |
Journal (paper) |
author |
Panagiotopoulou, Antigoni Anastassopoulos, Vassilis |
author_sort |
Panagiotopoulou, Antigoni |
title |
Scanned images resolution improvement using neural networks |
title_short |
Scanned images resolution improvement using neural networks |
title_full |
Scanned images resolution improvement using neural networks |
title_fullStr |
Scanned images resolution improvement using neural networks |
title_full_unstemmed |
Scanned images resolution improvement using neural networks |
title_sort |
scanned images resolution improvement using neural networks |
publishDate |
2011 |
url |
http://hdl.handle.net/10889/4840 |
work_keys_str_mv |
AT panagiotopoulouantigoni scannedimagesresolutionimprovementusingneuralnetworks AT anastassopoulosvassilis scannedimagesresolutionimprovementusingneuralnetworks |
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1799945014111895552 |