Local structure divergence index for image quality assessment
文献类型：会议论文
| 作者 | Gao, Fei ; Tao, Dacheng ; Li, Xuelong ; Gao, Xinbo ; He, Lihuo |
| 出版日期 | 2012 |
| 会议名称 | 19th international conference on neural information processing, iconip 2012 |
| 会议日期 | november 12, 2012 - november 15, 2012 |
| 会议地点 | doha, qatar |
| 页码 | 337-344 |
| 英文摘要 | image quality assessment (iqa) algorithms are important for image-processing systems. and structure information plays a significant role in the development of iqa metrics. in contrast to existing structure driven iqa algorithms that measure the structure information using the normalized image or gradient amplitudes, we present a new local structure divergence (lsd) index based on the local structures contained in an image. in particular, we exploit the steering kernels to describe local structures. afterward, we estimate the quality of a given image by calculating the symmetric kullback-leibler divergence (skld) between kernels of the reference image and the distorted image. experimental results on the live database ii show that lsd performs consistently with the human perception with a high confidence, and outperforms representative structure driven iqa metrics across various distortions. |
| 收录类别 | EI |
| 产权排序 | 3 |
| 会议主办者 | united development company psc (udc); qatar petrochemical company; exxonmobil; qatar petroleum; texas a and m university at qatar; asia pacific neural network assembly |
| 会议录 | neural information processing - 19th international conference, iconip 2012, proceedings
 |
| 会议录出版者 | springer verlag, tiergartenstrasse 17, heidelberg, d-69121, germany |
| 会议录出版地 | germany |
| 语种 | 英语 |
| ISSN号 | 3029743 |
| ISBN号 | 9783642344992 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/20541]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 推荐引用方式 GB/T 7714 | Gao, Fei,Tao, Dacheng,Li, Xuelong,et al. Local structure divergence index for image quality assessment[C]. 见:19th international conference on neural information processing, iconip 2012. doha, qatar. november 12, 2012 - november 15, 2012. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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