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Online multi-frame super-resolution of image sequences

作     者:Xu, Jieping Liang, Yonghui Liu, Jin Huang, Zongfu Liu, Xuewen 

作者机构:Space Engn Univ 1 Bayi Rd Beijing 101416 Peoples R China Natl Univ Def Technol Coll Optoelect Sci & Engn 109 Deya Rd Changsha 410073 Hunan Peoples R China 

出 版 物:《EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING》 (国际影象与视频处理杂志)

年 卷 期:2018年第2018卷第1期

页      面:1页

核心收录:

学科分类:0808[工学-电气工程] 1002[医学-临床医学] 0809[工学-电子科学与技术(可授工学、理学学位)] 08[工学] 

基  金:National Science Fund for Outstanding Young Scholars [2017-JCJQ-ZQ-005] 

主  题:Super-resolution Image processing Image sequences Online image processing 

摘      要:Multi-frame super-resolution recovers a high-resolution (HR) image from a sequence of low-resolution (LR) images. In this paper, we propose an algorithm that performs multi-frame super-resolution in an online fashion. This algorithm processes only one low-resolution image at a time instead of co-processing all LR images which is adopted by state-of-the-art super-resolution techniques. Our algorithm is very fast and memory efficient, and simple to implement. In addition, we employ a noise-adaptive parameter in the classical steepest gradient optimization method to avoid noise amplification and overfitting LR images. Experiments with simulated and real-image sequences yield promising results.

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