An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation

The use of edges to determine an optimal region of interest (ROI) location is increasingly becoming popular for image deblurring. Recent studies have shown that regions with strong edges tend to produce better deblurring results. In this study, a direct method for ROI localization based on edge r...

Full description

Saved in:

Bibliographic Details
Main Author:	Shapri, Ahmad Husni Mohd
Format:	Thesis
Language:	English
Published:	2019
Subjects:	T Technology
Online Access:	http://eprints.usm.my/48078/1/An%20Optimal%20Region%20Of%20Interest%20Localization%20Using%20Edge%20Refinement%20Filter%20And%20Entropy-Based%20Measurement%20For%20Point%20Spread%20Function%20Stimation.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-usm-ep.48078
record_format	uketd_dc
spelling	my-usm-ep.480782021-11-17T03:42:10Z An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation 2019-10-01 Shapri, Ahmad Husni Mohd T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering The use of edges to determine an optimal region of interest (ROI) location is increasingly becoming popular for image deblurring. Recent studies have shown that regions with strong edges tend to produce better deblurring results. In this study, a direct method for ROI localization based on edge refinement filter and entropy-based measurement is proposed. Using this method, the randomness of grey level distribution is quantitatively measured, from which the ROI is determined. This method has low computation cost since it contains no matrix operations. The proposed method has been tested using three sets of test images - Dataset I, II and III. Empirical results suggest that the improved edge refinement filter is competitive when compared to the established edge detection schemes and achieves better performance in the Pratt's figure-of-merit (PFoM) and the twofold consensus ground truth (TCGT); averaging at 15.7 % and 28.7 %, respectively. The novelty of the proposed approach lies in the use of this improved filtering strategy for accurate estimation of point spread function (PSF), and hence, a more precise image restoration. As a result, the proposed solutions compare favourably against existing techniques with the peak signal-to-noise ratio (PSNR), kernel similarity (KS) index, and error ratio (ER) averaging at 24.8 dB, 0.6 and 1.4, respectively. Additional experiments involving real blurred images demonstrated the competitiveness of the proposed approach in performing restoration in the absent of PSF. 2019-10 Thesis http://eprints.usm.my/48078/ http://eprints.usm.my/48078/1/An%20Optimal%20Region%20Of%20Interest%20Localization%20Using%20Edge%20Refinement%20Filter%20And%20Entropy-Based%20Measurement%20For%20Point%20Spread%20Function%20Stimation.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology T Technology
spellingShingle	T Technology T Technology Shapri, Ahmad Husni Mohd An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation
description	The use of edges to determine an optimal region of interest (ROI) location is increasingly becoming popular for image deblurring. Recent studies have shown that regions with strong edges tend to produce better deblurring results. In this study, a direct method for ROI localization based on edge refinement filter and entropy-based measurement is proposed. Using this method, the randomness of grey level distribution is quantitatively measured, from which the ROI is determined. This method has low computation cost since it contains no matrix operations. The proposed method has been tested using three sets of test images - Dataset I, II and III. Empirical results suggest that the improved edge refinement filter is competitive when compared to the established edge detection schemes and achieves better performance in the Pratt's figure-of-merit (PFoM) and the twofold consensus ground truth (TCGT); averaging at 15.7 % and 28.7 %, respectively. The novelty of the proposed approach lies in the use of this improved filtering strategy for accurate estimation of point spread function (PSF), and hence, a more precise image restoration. As a result, the proposed solutions compare favourably against existing techniques with the peak signal-to-noise ratio (PSNR), kernel similarity (KS) index, and error ratio (ER) averaging at 24.8 dB, 0.6 and 1.4, respectively. Additional experiments involving real blurred images demonstrated the competitiveness of the proposed approach in performing restoration in the absent of PSF.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Shapri, Ahmad Husni Mohd
author_facet	Shapri, Ahmad Husni Mohd
author_sort	Shapri, Ahmad Husni Mohd
title	An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation
title_short	An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation
title_full	An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation
title_fullStr	An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation
title_full_unstemmed	An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation
title_sort	optimal region of interest localization using edge refinement filter and entropy-based measurement for point spread function stimation
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik
publishDate	2019
url	http://eprints.usm.my/48078/1/An%20Optimal%20Region%20Of%20Interest%20Localization%20Using%20Edge%20Refinement%20Filter%20And%20Entropy-Based%20Measurement%20For%20Point%20Spread%20Function%20Stimation.pdf
_version_	1747821877847392256

An Optimal Region Of Interest Localization Using Edge Refinement Filter And Entropy-Based Measurement For Point Spread Function Stimation

Similar Items