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3D Comfort and Quality
Volume: 28 | Article ID: art00015
Image
An adaptive contrast enhancement method for stereo endoscopic images combining binocular just noticeable difference model and depth information
  DOI :  10.2352/ISSN.2470-1173.2016.13.IQSP-212  Published OnlineFebruary 2016
Abstract

Endoscopic image enhancement has become a very popular research field due to the success of minimally invasive interventions and the innovation of new technological treatment and diagnosis tools such as stereoscopic laparoscopes and the wireless capsule endoscopy. In spite of the important advances achieved in terms of image processing and enhancement, only a few techniques can be adapted to stereo endoscopic images. This can be explained by the specificities of the stereo endoscopic video acquisition process, the surgical tasks artifacts and the endoscopic domain characteristics (e.g., organ textures, edges, color distribution). In this paper we present a contrast enhancement method for stereo endoscopic images taking into consideration some of these specificities, namely those of the acquired stereo images i.e. the depth information, the binocular vision and the organs boundaries/textures. The idea is to enhance the image quality by a contrast enhancement process that exploits the local image activity, the depth information and the binocular just noticeable difference (BJND) model. The results of the conducted subjective experiment show that the proposed method produces stereo endoscopic images with sharper details of the underlying tissues and organs, without introducing any halo effect or overshooting. The observers reported as well a more depth feeling and less visual fatigue when perceiving the enhanced stereo endoscopic images.

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  Cite this article 

Bilel Sdiri, Azeddine Beghdadi, Faouzi Alaya Cheikh, Marius Pedersen, Ole Jakob Elle, "An adaptive contrast enhancement method for stereo endoscopic images combining binocular just noticeable difference model and depth informationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XIII,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.13.IQSP-212

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Electronic Imaging
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