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J. Imaging 2018, 4(6), 75; https://doi.org/10.3390/jimaging4060075

Stochastic Capsule Endoscopy Image Enhancement

1
Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway
2
Department of Gastroenterology, Innlandet Hospital Trust, Institute of Clinical Medicine, University of Oslo, 0315 Oslo, Norway
3
Department of Information Security and Communication Technology Norwegian University of Science and Technology, 2815 Gjøvik, Norway
*
Author to whom correspondence should be addressed.
Received: 25 March 2018 / Revised: 16 May 2018 / Accepted: 29 May 2018 / Published: 6 June 2018
(This article belongs to the Special Issue Computational Colour Imaging)
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Abstract

Capsule endoscopy, which uses a wireless camera to take images of the digestive tract, is emerging as an alternative to traditional colonoscopy. The diagnostic values of these images depend on the quality of revealed underlying tissue surfaces. In this paper, we consider the problem of enhancing the visibility of detail and shadowed tissue surfaces for capsule endoscopy images. Using concentric circles at each pixel for random walks combined with stochastic sampling, the proposed method enhances the details of vessel and tissue surfaces. The framework decomposes the image into two detailed layers that contain shadowed tissue surfaces and detail features. The target pixel value is recalculated for the smooth layer using similarity of the target pixel to neighboring pixels by weighting against the total gradient variation and intensity differences. In order to evaluate the diagnostic image quality of the proposed method, we used clinical subjective evaluation with a rank order on selected KID image database and compared it to state-of-the-art enhancement methods. The result showed that the proposed method provides a better result in terms of diagnostic image quality and objective quality contrast metrics and structural similarity index. View Full-Text
Keywords: capsule video endoscopy; stochastic sampling; random walks; color gradient; image decomposition capsule video endoscopy; stochastic sampling; random walks; color gradient; image decomposition
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Mohammed, A.; Farup, I.; Pedersen, M.; Hovde, Ø.; Yildirim Yayilgan, S. Stochastic Capsule Endoscopy Image Enhancement. J. Imaging 2018, 4, 75.

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