A retinal image sharpness metric based on histogram of edge width

Retinal image sharpness assessment is one of the critical requirements of automatic quality evaluation in telemedicine screening for diabetic retinopathy. In this paper, a new sharpness metric measuring the spread of edges is presented to quantify fundus image clarity. After edge detection on the re...

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Main Authors: Jia-Wen Lin, Qian Weng, Lan-Yan Xue, Xin-Rong Cao, Lun Yu
Format: Article
Language:English
Published: SAGE Publishing 2017-09-01
Series:Journal of Algorithms & Computational Technology
Online Access:https://doi.org/10.1177/1748301817713184
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spelling doaj-9a972cceb66740f084935bcdda86fd172020-11-25T03:16:58ZengSAGE PublishingJournal of Algorithms & Computational Technology1748-30181748-30262017-09-011110.1177/1748301817713184A retinal image sharpness metric based on histogram of edge widthJia-Wen Lin0Qian Weng1Lan-Yan Xue2Xin-Rong Cao3Lun Yu4College of Mathematics and Computer Science, Fuzhou University, Fuzhou, PR ChinaCollege of Mathematics and Computer Science, Fuzhou University, Fuzhou, PR ChinaCollege of Physics and Information Engineering, Fuzhou University, Fuzhou, PR ChinaCollege of Physics and Information Engineering, Fuzhou University, Fuzhou, PR ChinaCollege of Physics and Information Engineering, Fuzhou University, Fuzhou, PR ChinaRetinal image sharpness assessment is one of the critical requirements of automatic quality evaluation in telemedicine screening for diabetic retinopathy. In this paper, a new sharpness metric measuring the spread of edges is presented to quantify fundus image clarity. After edge detection on the region of interest of retinal image, the width of each edge is calculated and the histogram of region of interest generated. Based on the histogram, a distance-based factor is introduced to gain the weighted edge width, which is defined as the sharpness metric for the fundus image. The method was tested on Messidor dataset and a proprietary dataset. The results show that the proposed metric performs well over different image distortion levels and resolutions and is of low computational complexity. The weighted edge width value of gradable retinal image, which is irrelevant to resolution, is always within the range of 3–7 pixels.https://doi.org/10.1177/1748301817713184
collection DOAJ
language English
format Article
sources DOAJ
author Jia-Wen Lin
Qian Weng
Lan-Yan Xue
Xin-Rong Cao
Lun Yu
spellingShingle Jia-Wen Lin
Qian Weng
Lan-Yan Xue
Xin-Rong Cao
Lun Yu
A retinal image sharpness metric based on histogram of edge width
Journal of Algorithms & Computational Technology
author_facet Jia-Wen Lin
Qian Weng
Lan-Yan Xue
Xin-Rong Cao
Lun Yu
author_sort Jia-Wen Lin
title A retinal image sharpness metric based on histogram of edge width
title_short A retinal image sharpness metric based on histogram of edge width
title_full A retinal image sharpness metric based on histogram of edge width
title_fullStr A retinal image sharpness metric based on histogram of edge width
title_full_unstemmed A retinal image sharpness metric based on histogram of edge width
title_sort retinal image sharpness metric based on histogram of edge width
publisher SAGE Publishing
series Journal of Algorithms & Computational Technology
issn 1748-3018
1748-3026
publishDate 2017-09-01
description Retinal image sharpness assessment is one of the critical requirements of automatic quality evaluation in telemedicine screening for diabetic retinopathy. In this paper, a new sharpness metric measuring the spread of edges is presented to quantify fundus image clarity. After edge detection on the region of interest of retinal image, the width of each edge is calculated and the histogram of region of interest generated. Based on the histogram, a distance-based factor is introduced to gain the weighted edge width, which is defined as the sharpness metric for the fundus image. The method was tested on Messidor dataset and a proprietary dataset. The results show that the proposed metric performs well over different image distortion levels and resolutions and is of low computational complexity. The weighted edge width value of gradable retinal image, which is irrelevant to resolution, is always within the range of 3–7 pixels.
url https://doi.org/10.1177/1748301817713184
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