Local learning-based image super-resolution

Xiaoqiang Lu, Haoliang Yuan, Yuan Yuan, Pingkun Yan, Luoqing Li, Xuelong Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

12 引用 (Scopus)

摘要

Local learning algorithm has been widely used in single-frame super-resolution reconstruction algorithm, such as neighbor embedding algorithm [1] and locality preserving constraints algorithm [2]. Neighbor embedding algorithm is based on manifold assumption, which defines that the embedded neighbor patches are contained in a single manifold. While manifold assumption does not always hold. In this paper, we present a novel local learning-based image single-frame SR reconstruction algorithm with kernel ridge regression (KRR). Firstly, Gabor filter is adopted to extract texture information from low-resolution patches as the feature. Secondly, each input low-resolution feature patch utilizes K nearest neighbor algorithm to generate a local structure. Finally, KRR is employed to learn a map from input low-resolution (LR) feature patches to high-resolution (HR) feature patches in the corresponding local structure. Experimental results show the effectiveness of our method.

源语言英语
主期刊名MMSP 2011 - IEEE International Workshop on Multimedia Signal Processing
DOI
出版状态已出版 - 2011
已对外发布
活动3rd IEEE International Workshop on Multimedia Signal Processing, MMSP 2011 - Hangzhou, 中国
期限: 17 11月 201119 11月 2011

出版系列

姓名MMSP 2011 - IEEE International Workshop on Multimedia Signal Processing

会议

会议3rd IEEE International Workshop on Multimedia Signal Processing, MMSP 2011
国家/地区中国
Hangzhou
时期17/11/1119/11/11

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