Visible to the public Improving visual quality in wireless capsule endoscopy images with contrast-limited adaptive histogram equalization

TitleImproving visual quality in wireless capsule endoscopy images with contrast-limited adaptive histogram equalization
Publication TypeConference Paper
Year of Publication2015
AuthorsMoradi, M., Falahati, A., Shahbahrami, A., Zare-Hassanpour, R.
Conference Name2015 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA)
Date Publishedmar
Keywordsbiological organs, biomedical optical imaging, bowel diseases, Contrast Enhancement, contrast enhancement algorithm, contrast-limited adaptive histogram equalization, Diagnosis, diseases, edge strength similarity-for-image, endoscopes, gastrointestinal bleeding, gastrointestinal problem detection, Gastrointestinal tract, image denoising, image enhancement, Imaging, medical image processing, noninvasive device, peak signal-to-noise ratio, performance evaluation, polyps, PSNR, pubcrawl170111, Quality metrics, removing noise algorithm, similarity index measure, visual quality, WCE image quality, Wireless Capsule Endoscopy (WCE), wireless capsule endoscopy images, Wireless communication
Abstract

Wireless Capsule Endoscopy (WCE) is a noninvasive device for detection of gastrointestinal problems especially small bowel diseases, such as polyps which causes gastrointestinal bleeding. The quality of WCE images is very important for diagnosis. In this paper, a new method is proposed to improve the quality of WCE images. In our proposed method for improving the quality of WCE images, Removing Noise and Contrast Enhancement (RNCE) algorithm is used. The algorithm have been implemented and tested on some real images. Quality metrics used for performance evaluation of the proposed method is Structural Similarity Index Measure (SSIM), Peak Signal-to-Noise Ratio (PSNR) and Edge Strength Similarity for Image (ESSIM). The results obtained from SSIM, PSNR and ESSIM indicate that the implemented RNCE method improve the quality of WCE images significantly.

DOI10.1109/PRIA.2015.7161645
Citation Keymoradi_improving_2015