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Open Access An adaptive contrast enhancement method for stereo endoscopic images combining binocular just noticeable difference model and depth information

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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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Document Type: Research Article

Publication date: 01 February 2016

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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