Human visual perception-based image quality analyzer for assessment of contrast enhancement methods
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 Correl...
保存先:
| 第一著者: | |
|---|---|
| その他の著者: | |
| フォーマット: | 論文 |
| 出版事項: |
Zarka Private Univ
2023
|
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
| 要約: | 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. |
|---|