IEICE TRANSACTIONS on Fundamentals
Image Quality Improvement for Capsule Endoscopy Based on Compressed Sensing with K-SVD Dictionary Learning
Summary :
Reducing the power consumption of capsule endoscopy is essential for its further development. We introduce K-SVD dictionary learning to design a dictionary for sparse coding, and improve reconstruction accuracy of capsule endoscopic images captured using compressed sensing. At a compression ratio of 20%, the proposed method improves image quality by approximately 4.4 dB for the peak signal-to-noise ratio.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E105-A No.4 pp.743-747
- Publication Date
- 2022/04/01
- Publicized
- 2021/10/01
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2021EAL2033
- Type of Manuscript
- LETTER
- Category
- Image
Authors
Yuuki HARADA
Osaka University
Daisuke KANEMOTO
Osaka University
Takahiro INOUE
Osaka University
Osamu MAIDA
Osaka University
Tetsuya HIROSE
Osaka University
Keyword
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Yuuki HARADA, Daisuke KANEMOTO, Takahiro INOUE, Osamu MAIDA, Tetsuya HIROSE, "Image Quality Improvement for Capsule Endoscopy Based on Compressed Sensing with K-SVD Dictionary Learning" in IEICE TRANSACTIONS on Fundamentals,
vol. E105-A, no. 4, pp. 743-747, April 2022, doi: 10.1587/transfun.2021EAL2033.
Abstract: Reducing the power consumption of capsule endoscopy is essential for its further development. We introduce K-SVD dictionary learning to design a dictionary for sparse coding, and improve reconstruction accuracy of capsule endoscopic images captured using compressed sensing. At a compression ratio of 20%, the proposed method improves image quality by approximately 4.4 dB for the peak signal-to-noise ratio.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2021EAL2033/_p
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@ARTICLE{e105-a_4_743,
author={Yuuki HARADA, Daisuke KANEMOTO, Takahiro INOUE, Osamu MAIDA, Tetsuya HIROSE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Image Quality Improvement for Capsule Endoscopy Based on Compressed Sensing with K-SVD Dictionary Learning},
year={2022},
volume={E105-A},
number={4},
pages={743-747},
abstract={Reducing the power consumption of capsule endoscopy is essential for its further development. We introduce K-SVD dictionary learning to design a dictionary for sparse coding, and improve reconstruction accuracy of capsule endoscopic images captured using compressed sensing. At a compression ratio of 20%, the proposed method improves image quality by approximately 4.4 dB for the peak signal-to-noise ratio.},
keywords={},
doi={10.1587/transfun.2021EAL2033},
ISSN={1745-1337},
month={April},}
Copy
TY - JOUR
TI - Image Quality Improvement for Capsule Endoscopy Based on Compressed Sensing with K-SVD Dictionary Learning
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 743
EP - 747
AU - Yuuki HARADA
AU - Daisuke KANEMOTO
AU - Takahiro INOUE
AU - Osamu MAIDA
AU - Tetsuya HIROSE
PY - 2022
DO - 10.1587/transfun.2021EAL2033
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E105-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2022
AB - Reducing the power consumption of capsule endoscopy is essential for its further development. We introduce K-SVD dictionary learning to design a dictionary for sparse coding, and improve reconstruction accuracy of capsule endoscopic images captured using compressed sensing. At a compression ratio of 20%, the proposed method improves image quality by approximately 4.4 dB for the peak signal-to-noise ratio.
ER -
English
