Abstract
This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable free parameters, which are constructed based on an integer version of Haar transform. Our learning method is to determine such free parameters using some subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet transform has the feature of the subimages. We apply such a wavelet transform to high frequency components of a reference image and check whether they are vanished or not, to detect a target subimage.
| Original language | English |
|---|---|
| Pages | 403-406 |
| Number of pages | 4 |
| Publication status | Published - Dec 1 2000 |
| Event | International Conference on Image Processing (ICIP 2000) - Vancouver, BC, Canada Duration: Sep 10 2000 → Sep 13 2000 |
Other
| Other | International Conference on Image Processing (ICIP 2000) |
|---|---|
| Country | Canada |
| City | Vancouver, BC |
| Period | 9/10/00 → 9/13/00 |
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All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
Cite this
Subimage extraction by integer-type lifting wavelet transforms. / Takano, Shigeru; Niijima, K.
2000. 403-406 Paper presented at International Conference on Image Processing (ICIP 2000), Vancouver, BC, Canada.Research output: Contribution to conference › Paper
}
TY - CONF
T1 - Subimage extraction by integer-type lifting wavelet transforms
AU - Takano, Shigeru
AU - Niijima, K.
PY - 2000/12/1
Y1 - 2000/12/1
N2 - This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable free parameters, which are constructed based on an integer version of Haar transform. Our learning method is to determine such free parameters using some subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet transform has the feature of the subimages. We apply such a wavelet transform to high frequency components of a reference image and check whether they are vanished or not, to detect a target subimage.
AB - This paper proposes a method for extracting subimages from a huge reference image by using lifting wavelet transforms that map integers to integers. Our integer-type lifting wavelet transform contains controllable free parameters, which are constructed based on an integer version of Haar transform. Our learning method is to determine such free parameters using some subimages so as to vanish their high frequency components in the y- and x-directions. The learnt wavelet transform has the feature of the subimages. We apply such a wavelet transform to high frequency components of a reference image and check whether they are vanished or not, to detect a target subimage.
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