Image Quality Improvement for Capsule Endoscopy Based on Compressed Sensing with K-SVD Dictionary Learning

Image Quality Improvement for Capsule Endoscopy Based on Compressed Sensing with K-SVD Dictionary Learning

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...

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Veröffentlicht in:IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences Communications and Computer Sciences, 2022/04/01, Vol.E105.A(4), pp.743-747
Hauptverfasser: HARADA, Yuuki, KANEMOTO, Daisuke, INOUE, Takahiro, MAIDA, Osamu, HIROSE, Tetsuya
Format: Artikel
Sprache:eng
Schlagworte:
capsule endoscopy
compressed sensing
Compression ratio
Dictionaries
Endoscopy
high quality
Image compression
Image quality
Image reconstruction
K-SVD
Learning
Power consumption
Signal to noise ratio
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Beschreibung
Zusammenfassung: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.
ISSN:0916-8508
1745-1337
DOI:10.1587/transfun.2021EAL2033