The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article propose une méthode d'extraction de sous-images à partir d'une immense image de référence par l'apprentissage de filtres d'ondelettes de levage. Les filtres à ondelettes liftantes sont des filtres à ondelettes biorthogonaux contenant des paramètres libres développés par Sweldens. Notre méthode consiste à apprendre ces paramètres libres en utilisant certaines sous-images d'entraînement afin de faire disparaître leurs composantes haute fréquence dans le y- Et x-directions. Les filtres d'ondelettes appris ont la particularité d'entraîner des sous-images. En appliquant de tels filtres d'ondelettes à l'image de référence, nous pouvons détecter les emplacements où les composantes haute fréquence sont presque les mêmes que celles de la sous-image cible.
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Shigeru TAKANO, Koichi NIIJIMA, "Extraction of Subimages by Lifting Wavelet Filters" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 8, pp. 1559-1565, August 2000, doi: .
Abstract: This paper proposes a method for extracting subimages from a huge reference image by learning lifting wavelet filters. Lifting wavelet filters are biorthogonal wavelet filters containing free parameters developed by Sweldens. Our method is to learn such free parameters using some training subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet filters have the feature of training subimages. Applying such wavelet filters to the reference image, we can detect the locations where the high frequency components are almost the same as those of the target subimage.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_8_1559/_p
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@ARTICLE{e83-a_8_1559,
author={Shigeru TAKANO, Koichi NIIJIMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Extraction of Subimages by Lifting Wavelet Filters},
year={2000},
volume={E83-A},
number={8},
pages={1559-1565},
abstract={This paper proposes a method for extracting subimages from a huge reference image by learning lifting wavelet filters. Lifting wavelet filters are biorthogonal wavelet filters containing free parameters developed by Sweldens. Our method is to learn such free parameters using some training subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet filters have the feature of training subimages. Applying such wavelet filters to the reference image, we can detect the locations where the high frequency components are almost the same as those of the target subimage.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Extraction of Subimages by Lifting Wavelet Filters
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1559
EP - 1565
AU - Shigeru TAKANO
AU - Koichi NIIJIMA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2000
AB - This paper proposes a method for extracting subimages from a huge reference image by learning lifting wavelet filters. Lifting wavelet filters are biorthogonal wavelet filters containing free parameters developed by Sweldens. Our method is to learn such free parameters using some training subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet filters have the feature of training subimages. Applying such wavelet filters to the reference image, we can detect the locations where the high frequency components are almost the same as those of the target subimage.
ER -