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DC Field | Value | Language |
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dc.contributor.author | Chen, S.-D. | |
dc.date.accessioned | 2018-03-22T03:06:17Z | - |
dc.date.available | 2018-03-22T03:06:17Z | - |
dc.date.issued | 2016 | |
dc.identifier.uri | http://dspace.uniten.edu.my/jspui/handle/123456789/10125 | - |
dc.description.abstract | Absolute Mean Brightness Error (AMBE) and entropy are two popular Image Quality Analyzer (IQA) metrics used for assessment of Histogram Equalization (HE)-based contrast enhancement methods. However, recent study shows that they have poor correlation with Human Visual Perception (HVP); Pearson Correlation Coefficient (PCC)<0.4. This paper, proposed a new IQA which takes into account important properties of HVP with respect to luminance, texture and scale. evaluation results show that the proposed IQA has significantly improved performance (PCC>0.9). It outperforms all IQAs in study, including two prominent IQAs designed for assessment of image fidelity in image coding-Multi-Scale Structural Similarity (MSSIM) and information fidelity criterion. © 2016, Zarka Private Univ. All rights reserved. | |
dc.title | Human visual perception-based image quality analyzer for assessment of contrast enhancement methods | |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
Appears in Collections: | COGS Scholarly Publication |
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