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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Series: | Journal of Algorithms & Computational Technology |
Online Access: | https://doi.org/10.1177/1748301817713184 |
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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 |
work_keys_str_mv |
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