Abstract
Image quality assessment (IQA) is provided as computational models to measure the quality of images in perceptually consistent manner. In this paper, a novel image quality index with highlighting shape of histogram of the image targeted is introduced to assess image qualities. The index will be used in place of existing traditional Universal Image Quality Index (UIQI) “in one go”. It offers extra information about the distortion between an original image and a distorted image in comparisons with UIQI. The proposed index is designed based on modelling image distortion combinations of four major factors: loss of correlation, luminance distortion, contrast distortion and shape distortion. This index is easy to calculate and applicable in various image processing applications. Experimental results show that the proposed image quality index plays a significantly role in the quality evaluation on the open source “Wireless Imaging Quality (WIQ) database”.
| Original language | English |
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| Title of host publication | International Conference on Neural Information Processing (ICONIP 2013) |
| Subtitle of host publication | Lecture Notes in Computer Science |
| Editors | Minho Lee, Akira Hirose, Zeng Guang Hou, Rhee Man Kil |
| Place of Publication | Korea |
| Publisher | Springer |
| Pages | 549-556 |
| Number of pages | 8 |
| Volume | 8228 |
| ISBN (Electronic) | 9783642420511 |
| ISBN (Print) | 9783642420504 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 20th International Conference on Neural Information Processing (ICONIP 2013) - Daegu, Daegu, Korea, Republic of Duration: 3 Nov 2013 → 7 Nov 2013 |
Conference
| Conference | 20th International Conference on Neural Information Processing (ICONIP 2013) |
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| Abbreviated title | ICONIP 2013 |
| Country/Territory | Korea, Republic of |
| City | Daegu |
| Period | 3/11/13 → 7/11/13 |