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A Local Texture-Constrained Super-Resolution Method
Qingjie Liu; Yunhong Wang; Zhaoxiang Zhang
2012-12-04
会议名称Pacific-Rim Conference on Multimedia
会议录名称PCM 2012
会议日期4-6 December 2012
会议地点Singapore, Singapore
摘要This 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.
关键词Image Super-resolution Lbp Neighbor Embedding Ssim
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/13256
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
推荐引用方式
GB/T 7714
Qingjie Liu,Yunhong Wang,Zhaoxiang Zhang. A Local Texture-Constrained Super-Resolution Method[C],2012.
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