Image quality assessment using edge based features
Image quality assessment using edge based features
There are many applications for Image Quality Assessment (IQA) in digital image processing. Many techniques have been proposed to measure the quality of an image such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), and Mean Structural Similarity Index Measurement (MSSIM). In this paper, a new technique, namely, Edge Based Image Quality Assessments (EBIQA) is proposed. The proposed technique is based on different edge features which are extracted from original (distortion free) and distorted images. The new approach was implemented and tested using different images which have been taken from A57 and WIQ image databases. The experimental results show that the functionality of the EBIQA technique is better than the state of art IQA techniques. The proposed technique is consistent with the mean opinion score which makes it suitable for automatic image quality assessment.
Edge based features, Full reference, Image quality assessment
7407-7422
Attar, Abdolrahman
f5efd538-042a-4647-9d46-1370d3049b72
Shahbahrami, Asadollah
a254cee0-48b1-4a87-b6ab-49bf8aee412d
Rad, Reza Moradi
7cf68458-1991-4d35-96dc-b6433caeb6f9
1 June 2016
Attar, Abdolrahman
f5efd538-042a-4647-9d46-1370d3049b72
Shahbahrami, Asadollah
a254cee0-48b1-4a87-b6ab-49bf8aee412d
Rad, Reza Moradi
7cf68458-1991-4d35-96dc-b6433caeb6f9
Attar, Abdolrahman, Shahbahrami, Asadollah and Rad, Reza Moradi
(2016)
Image quality assessment using edge based features.
Multimedia Tools and Applications, 75 (12), .
(doi:10.1007/s11042-015-2663-9).
Abstract
There are many applications for Image Quality Assessment (IQA) in digital image processing. Many techniques have been proposed to measure the quality of an image such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), and Mean Structural Similarity Index Measurement (MSSIM). In this paper, a new technique, namely, Edge Based Image Quality Assessments (EBIQA) is proposed. The proposed technique is based on different edge features which are extracted from original (distortion free) and distorted images. The new approach was implemented and tested using different images which have been taken from A57 and WIQ image databases. The experimental results show that the functionality of the EBIQA technique is better than the state of art IQA techniques. The proposed technique is consistent with the mean opinion score which makes it suitable for automatic image quality assessment.
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Published date: 1 June 2016
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Publisher Copyright:
© 2015, Springer Science+Business Media New York.
Keywords:
Edge based features, Full reference, Image quality assessment
Identifiers
Local EPrints ID: 480903
URI: http://eprints.soton.ac.uk/id/eprint/480903
ISSN: 1380-7501
PURE UUID: c7549bf8-23c6-4476-9e1b-c175518da738
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Date deposited: 10 Aug 2023 16:52
Last modified: 17 Mar 2024 01:12
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Contributors
Author:
Abdolrahman Attar
Author:
Asadollah Shahbahrami
Author:
Reza Moradi Rad
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