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Dynamic Searching and Classification for Highlight Removal on Endoscopic Image
- Source :
- Procedia Computer Science. 107:762-767
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- Endoscopic imaging is a common clinical modality to inspect surficial abnormality grew on the internal organs inside human body. Covered by tissue fluid, surface of these anatomies tend to be glossy, showing specular reflections from the illumination source. In this paper, we present a novel method for specular region separation and restoration from only a single image. Distinguishing from segmentation methods using simple threshold, our solution treats the separation of highlight pixels as a binarization problem based upon a supervised learning classification algorithm. Also, we propose a multiscale dynamic image expansion and fusion based method to restore the highlighted region. It takes full advantages of propagating the regions with similar structure features to specular regions. Experimental results on the removal of the endoscopic image with specular reflections demonstrate improved efficiency by the proposed method compared to commonly used techniques.
- Subjects :
- Modality (human–computer interaction)
genetic structures
Pixel
business.industry
Computer science
Pattern recognition
02 engineering and technology
01 natural sciences
Image (mathematics)
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
General Earth and Planetary Sciences
020201 artificial intelligence & image processing
Segmentation
Computer vision
sense organs
Specular reflection
Artificial intelligence
010306 general physics
business
Image restoration
General Environmental Science
Endoscopic image
Subjects
Details
- ISSN :
- 18770509
- Volume :
- 107
- Database :
- OpenAIRE
- Journal :
- Procedia Computer Science
- Accession number :
- edsair.doi...........fa891ef92d96ea4bdd04d8c081be0764