High Frequency Super-Resolution for Image Enhancement

被引：0

作者：

Lee, Oh-Young ^{[1
]}

Park, Sae-Jin ^{[1
]}

Kim, Jae-Woo ^{[1
]}

Kim, Jong-Ok ^{[1
]}

机构：

[1] Korea Univ, Sch Elect Engn, Seoul, South Korea

来源：

18TH IEEE INTERNATIONAL SYMPOSIUM ON CONSUMER ELECTRONICS (ISCE 2014) | 2014年

关键词：

multi-frame SR; high frequency SR; spatially weighted bilateral total variance; image enhancement;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Bayesian based MF-SR (multi-frame super-resolution) has been used as a popular and effective SR model. However, texture region is not reconstructed sufficiently because it works on the spatial domain. In this paper, we extend the MF-SR method to operate on the frequency domain for the improvement of HF information as much as possible. For this, we propose a spatially weighted bilateral total variation model as a regularization term for Bayesian estimation. Experimental results show that the proposed method can recover texture region with reduced noise, compared to conventional methods.

引用

页数：2

共 3 条

[1] Fast and robust multiframe super resolution
Farsiu, S
Robinson, MD
Elad, M
Milanfar, P
[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2004, 13 (10) : 1327 - 1344
[2] Super-resolution image reconstruction techniques: Trade-offs between the data-fidelity and regularization terms
Panagiotopoulou, Antigoni
Anastassopoulos, Vassilis
[J]. INFORMATION FUSION, 2012, 13 (03) : 185 - 195
[3] Multiframe Super-Resolution Employing a Spatially Weighted Total Variation Model
Yuan, Qiangqiang
Zhang, Liangpei
Shen, Huanfeng
[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2012, 22 (03) : 379 - 392

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