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 xdirections. 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.
| Original language | English |
|---|---|
| Pages (from-to) | 1559-1564 |
| Number of pages | 6 |
| Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
| Volume | E82-A |
| Issue number | 8 |
| Publication status | Published - Jan 1 2000 |
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All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics
Cite this
Extraction of subimages by lifting wavelet filters. / Takano, Shigeru; Niijima, Koichi.
In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E82-A, No. 8, 01.01.2000, p. 1559-1564.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Extraction of subimages by lifting wavelet filters
AU - Takano, Shigeru
AU - Niijima, Koichi
PY - 2000/1/1
Y1 - 2000/1/1
N2 - 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 xdirections. 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.
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 xdirections. 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.
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M3 - Article
AN - SCOPUS:0034250973
VL - E82-A
SP - 1559
EP - 1564
JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
SN - 0916-8508
IS - 8
ER -