CASIA OpenIR  > 类脑智能研究中心
A Local Texture-Constrained Super-Resolution Method
Qingjie Liu; Yunhong Wang; Zhaoxiang Zhang
2012-12-04
Conference NamePacific-Rim Conference on Multimedia
Source PublicationPCM 2012
Conference Date4-6 December 2012
Conference PlaceSingapore, Singapore
AbstractThis paper proposes a local texture constrained super-resolution method for the reconstruction of high-resolution image. Through the learned low/high-resolution patches from training images, the intended high resolution patches are reconstructed using neighbor embedding method. The major contributions of this paper are: 1) Local Binary Pattern (LBP) is adopted to classify the patches into different categories, only those patches who have the same pattern with the input patches are used as candidates; 2) Structural SIMilarity (SSIM) metric which can find the patches with texture most similar to the input is used to search the k most suitable patches in the corresponding category. Experiments show that LBP index can provide proper candidate patches and SSIM metric is better than other metric in finding the most texture similarity patches.
KeywordImage Super-resolution Lbp Neighbor Embedding Ssim
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13256
Collection类脑智能研究中心
Corresponding AuthorZhaoxiang Zhang
Recommended Citation
GB/T 7714
Qingjie Liu,Yunhong Wang,Zhaoxiang Zhang. A Local Texture-Constrained Super-Resolution Method[C],2012.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Qingjie Liu]'s Articles
[Yunhong Wang]'s Articles
[Zhaoxiang Zhang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Qingjie Liu]'s Articles
[Yunhong Wang]'s Articles
[Zhaoxiang Zhang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Qingjie Liu]'s Articles
[Yunhong Wang]'s Articles
[Zhaoxiang Zhang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.