QQ客服 官方微博 反馈留言

	Segmentation-based scale-invariant nonlocal means super resolution
	Yang, Saboya ; Liu, Jiaying ; Li, Qiaochu ; Guo, Zongming
	2014
英文摘要	Zooming in/out appears frequently in video shooting, which makes scale vary between frames. And object motion in videos may cause scale change of the object. It leads to the difficulty in finding similar patches and causes the invalidation of nonlocal means super resolution (NLM SR). In this paper, we propose a novel scale-compensated NLM SR algorithm. First, by considering the parameter model, the image is segmented in order to detect regions with different scales. Then, scale variations in different regions are computed based on SIFT descriptor. And patches extracted from different regions are compensated into the same scale to eliminate the effect of scale change. It is shown by experimental results that our proposed algorithm achieves the average PSNR by up to 0.678dB comparing with the state-of-the-art methods. Subjective results demonstrate the proposed method reduces artifacts and preserves more details. ? 2014 IEEE.; EI; 0
语种	英语
DOI标识	10.1109/ISCAS.2014.6865333
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/321443]
专题	计算机科学技术研究所
推荐引用方式 GB/T 7714	Yang, Saboya,Liu, Jiaying,Li, Qiaochu,et al. Segmentation-based scale-invariant nonlocal means super resolution. 2014-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。