IEICE TRANSACTIONS on Fundamentals
Denoising of Multi-Modal Images with PCA Self-Cross Bilateral Filter
Summary :
We present the PCA self-cross bilateral filter for denoising multi-modal images. We firstly apply the principal component analysis for input multi-modal images. We next smooth the first principal component with a preliminary filter and use it as a supplementary image for cross bilateral filtering of input images. Among some preliminary filters, the undecimated wavelet transform is useful for effective denoising of various multi-modal images such as color, multi-lighting and medical images.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E93-A No.9 pp.1709-1712
- Publication Date
- 2010/09/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E93.A.1709
- Type of Manuscript
- LETTER
- Category
- Image
Authors
Keyword
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Yu QIU, Kiichi URAHAMA, "Denoising of Multi-Modal Images with PCA Self-Cross Bilateral Filter" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 9, pp. 1709-1712, September 2010, doi: 10.1587/transfun.E93.A.1709.
Abstract: We present the PCA self-cross bilateral filter for denoising multi-modal images. We firstly apply the principal component analysis for input multi-modal images. We next smooth the first principal component with a preliminary filter and use it as a supplementary image for cross bilateral filtering of input images. Among some preliminary filters, the undecimated wavelet transform is useful for effective denoising of various multi-modal images such as color, multi-lighting and medical images.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.1709/_p
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@ARTICLE{e93-a_9_1709,
author={Yu QIU, Kiichi URAHAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Denoising of Multi-Modal Images with PCA Self-Cross Bilateral Filter},
year={2010},
volume={E93-A},
number={9},
pages={1709-1712},
abstract={We present the PCA self-cross bilateral filter for denoising multi-modal images. We firstly apply the principal component analysis for input multi-modal images. We next smooth the first principal component with a preliminary filter and use it as a supplementary image for cross bilateral filtering of input images. Among some preliminary filters, the undecimated wavelet transform is useful for effective denoising of various multi-modal images such as color, multi-lighting and medical images.},
keywords={},
doi={10.1587/transfun.E93.A.1709},
ISSN={1745-1337},
month={September},}
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TY - JOUR
TI - Denoising of Multi-Modal Images with PCA Self-Cross Bilateral Filter
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1709
EP - 1712
AU - Yu QIU
AU - Kiichi URAHAMA
PY - 2010
DO - 10.1587/transfun.E93.A.1709
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2010
AB - We present the PCA self-cross bilateral filter for denoising multi-modal images. We firstly apply the principal component analysis for input multi-modal images. We next smooth the first principal component with a preliminary filter and use it as a supplementary image for cross bilateral filtering of input images. Among some preliminary filters, the undecimated wavelet transform is useful for effective denoising of various multi-modal images such as color, multi-lighting and medical images.
ER -
English
