Naturalization of Screen Content Images for Enhanced Quality Evaluation
The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter pr...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2017
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/81486 http://hdl.handle.net/10220/43487 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| id |
sg-ntu-dr.10356-81486 |
|---|---|
| record_format |
dspace |
| spelling |
sg-ntu-dr.10356-814862020-03-07T11:48:52Z Naturalization of Screen Content Images for Enhanced Quality Evaluation Guo, Xingge Huang, Liping Gu, Ke Li, Leida Zhou, Zhili Tang, Lu School of Computer Science and Engineering Image quality assessment Screen content image The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter presents a simple and effective method to naturalize SCIs, so that the traditional quality models can be applied for SCI quality prediction. Specifically, bicubic interpolation-based up-sampling is proposed to achieve this goal. Extensive experiments and comparisons demonstrate the effectiveness of the proposed method. Published version 2017-07-28T02:51:44Z 2019-12-06T14:32:02Z 2017-07-28T02:51:44Z 2019-12-06T14:32:02Z 2017 Journal Article Guo, X., Huang, L., Gu, K., Li, L., Zhou, Z., & Tang, Lu. (2017). Naturalization of Screen Content Images for Enhanced Quality Evaluation. IEICE Transactions on Information and Systems, E100.D(3), 574-577. 0916-8532 https://hdl.handle.net/10356/81486 http://hdl.handle.net/10220/43487 10.1587/transinf.2016EDL8178 en IEICE Transactions on Information and Systems © 2017 Institute of Electronics, Information and Communication Engineers (IEICE). This paper was published in IEICE Transactions on Information and Systems and is made available as an electronic reprint (preprint) with permission of Institute of Electronics, Information and Communication Engineers (IEICE). The published version is available at: [http://dx.doi.org/10.1587/transinf.2016EDL8178]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 4 p. application/pdf |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| country |
Singapore |
| collection |
DR-NTU |
| language |
English |
| topic |
Image quality assessment Screen content image |
| spellingShingle |
Image quality assessment Screen content image Guo, Xingge Huang, Liping Gu, Ke Li, Leida Zhou, Zhili Tang, Lu Naturalization of Screen Content Images for Enhanced Quality Evaluation |
| description |
The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter presents a simple and effective method to naturalize SCIs, so that the traditional quality models can be applied for SCI quality prediction. Specifically, bicubic interpolation-based up-sampling is proposed to achieve this goal. Extensive experiments and comparisons demonstrate the effectiveness of the proposed method. |
| author2 |
School of Computer Science and Engineering |
| author_facet |
School of Computer Science and Engineering Guo, Xingge Huang, Liping Gu, Ke Li, Leida Zhou, Zhili Tang, Lu |
| format |
Article |
| author |
Guo, Xingge Huang, Liping Gu, Ke Li, Leida Zhou, Zhili Tang, Lu |
| author_sort |
Guo, Xingge |
| title |
Naturalization of Screen Content Images for Enhanced Quality Evaluation |
| title_short |
Naturalization of Screen Content Images for Enhanced Quality Evaluation |
| title_full |
Naturalization of Screen Content Images for Enhanced Quality Evaluation |
| title_fullStr |
Naturalization of Screen Content Images for Enhanced Quality Evaluation |
| title_full_unstemmed |
Naturalization of Screen Content Images for Enhanced Quality Evaluation |
| title_sort |
naturalization of screen content images for enhanced quality evaluation |
| publishDate |
2017 |
| url |
https://hdl.handle.net/10356/81486 http://hdl.handle.net/10220/43487 |
| _version_ |
1681047372944113664 |