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7 December 2016 Improved structural similarity metric for the visible quality measurement of images
Daeho Lee, Sungsoo Lim
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Journal of Electronic Imaging, Vol. 25, Issue 6, 063015 (December 2016). https://doi.org/10.1117/1.JEI.25.6.063015
Abstract
The visible quality assessment of images is important to evaluate the performance of image processing methods such as image correction, compressing, and enhancement. The structural similarity is widely used to determine the visible quality; however, existing structural similarity metrics cannot correctly assess the perceived human visibility of images that have been slightly geometrically transformed or images that have undergone significant regional distortion. We propose an improved structural similarity metric that is more close to human visible evaluation. Compared with the existing metrics, the proposed method can more correctly evaluate the similarity between an original image and various distorted images.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Daeho Lee and Sungsoo Lim "Improved structural similarity metric for the visible quality measurement of images," Journal of Electronic Imaging 25(6), 063015 (7 December 2016). https://doi.org/10.1117/1.JEI.25.6.063015
Published: 7 December 2016
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Cited by 13 scholarly publications.
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KEYWORDS
Quality measurement
Image quality
Image compression
Molybdenum
Distortion
Image filtering
Linear filtering
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