Endoscopic image enhancement with noise suppression. Issue 5 (14th September 2018)

• Record Type: Journal Article
• Authors: Xia, Wenyao; Chen, Elvis C.S.; Peters, Terry
• Is Part Of: Healthcare technology letters. Volume 5:Issue 5(2018)
• Page Start: 154
• Page End: 157
• Publication Date: 2018-09-14
• Subjects: endoscopes -- image processing -- biomedical optical imaging -- medical image processing -- medical robotics -- image enhancement -- surgery; low‐light region -- low signal‐to‐noise ratio -- heavy noise amplification -- endoscopic image enhancement -- different illumination regions -- enhancement design criteria -- desired image quality -- existing image enhancement methods -- image enhancement process -- endoscopic surgery -- naturalness image quality evaluator -- illumination index -- noise suppression -- stereoscopic endoscopes -- minimally invasive surgery -- surgical tools -- insufficient light sources -- irregular light sources -- image processing algorithms; Biomedical engineering -- Periodicals; Medical technology -- Periodicals; 610.28
• DOI: 10.1049/htl.2018.5067
• Languages: English
• ISSNs: 2053-3713

Abstract

Abstract : Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insufficient and irregular light sources become major challenges for endoscopic surgery. Not only do these conditions hinder image processing algorithms, sometimes surgical tools are barely visible when operating within low‐light regions. In addition, low‐light regions have low signal‐to‐noise ratio and metrication artefacts due to quantisation errors. As a result, present image enhancement methods usually suffer from heavy noise amplification in low‐light regions. In this Letter, the authors propose an effective method for endoscopic image enhancement by identifying different illumination regions and designing the enhancement design criteria for desired image quality. Compared with existing image enhancement methods, the proposed method is able to enhance the low‐light region while preventing noise amplification during image enhancement process. The proposed method is tested with 200 images acquired by endoscopic surgeries. Computed results show that the proposed algorithm can outperform state‐of‐the‐art algorithms for image enhancement, in terms of naturalness image quality evaluator and illumination index.