Stochastic Capsule Endoscopy Image Enhancement

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...

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Bibliographic Details
Published in:Journal of imaging 2018-06, Vol.4 (6), p.75
Main Authors: Mohammed, Ahmed, Farup, Ivar, Pedersen, Marius, Hovde, Øistein, Yildirim Yayilgan, Sule
Format: Article
Language:English
Subjects:
Algorithms
capsule video endoscopy
Colonoscopy
color gradient
Diagnostic systems
Endoscopy
Image contrast
image decomposition
Image enhancement
Image quality
International conferences
Methods
Pixels
Quality
Random walk
random walks
Similarity
State of the art
stochastic sampling
Visibility
Wavelet transforms
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Summary: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.
ISSN:2313-433X
2313-433X
DOI:10.3390/jimaging4060075