A no-reference objective image sharpness metric based on a filter bank of Gaussian derivative wavelets

2011 ◽  
Author(s):  
Chengho Hsin ◽  
Jr-Wei Jang ◽  
Shaw-Jyh Shin ◽  
Shin-Hsien Chen
Keyword(s):  
Filter Bank ◽  
Image Sharpness ◽  
Gaussian Derivative ◽  
Sharpness Metric

A No-Reference Objective Image Sharpness Metric Based on a Filter Bank of Gaussian Derivative Wavelets

2011 ◽  
Vol 1 (2) ◽  
pp. 83-87
Author(s):  
Chengho Hsin ◽  
Jr-Wei Jang ◽  
Shaw-Jyh Shin ◽  
Shin-Hsien Chen
Keyword(s):  
Filter Bank ◽  
Image Sharpness ◽  
Gaussian Derivative ◽  
Sharpness Metric

An image sharpness metric for image processing applications using feedback

2007 ◽  
Author(s):  
Eric P. Lam ◽  
Christopher A. Leddy ◽  
Stephen R. Nash
Keyword(s):  
Image Processing ◽  
Image Sharpness ◽  
Sharpness Metric

scholarly journals A retinal image sharpness metric based on histogram of edge width

2017 ◽  
Vol 11 (3) ◽  
pp. 292-300 ◽  
Author(s):  
Jia-Wen Lin ◽  
Qian Weng ◽  
Lan-Yan Xue ◽  
Xin-Rong Cao ◽  
Lun Yu
Keyword(s):  
Diabetic Retinopathy ◽  
Computational Complexity ◽  
Edge Detection ◽  
Retinal Image ◽  
Quality Evaluation ◽  
Region Of Interest ◽  
Fundus Image ◽  
Image Sharpness ◽  
Low Computational Complexity ◽  
Sharpness Metric

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.

A Perceptual Image Sharpness Metric Based on Local Edge Gradient Analysis

2013 ◽  
Vol 20 (4) ◽  
pp. 379-382 ◽  
Author(s):  
C. Feichtenhofer ◽  
H. Fassold ◽  
P. Schallauer
Keyword(s):  
Gradient Analysis ◽  
Image Sharpness ◽  
Sharpness Metric ◽  
Local Edge
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