A remote sensing image destriping model based on low-rank and directional sparse constraint

doi:10.3390/rs13245126

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所

	A remote sensing image destriping model based on low-rank and directional sparse constraint
	X. Wu; H. Qu; L. Zheng; T. Gao and Z. Zhang
刊名	Remote Sensing
	2021
卷号	13 期号:24
ISSN号	20724292
DOI	10.3390/rs13245126
英文摘要	Stripe noise is a common condition that has a considerable impact on the quality of the images. Therefore, stripe noise removal (destriping) is a tremendously important step in image processing. Since the existing destriping models cause different degrees of ripple effects, in this paper a new model, based on total variation (TV) regularization, global low rank and directional sparsity constraints, is proposed for the removal of vertical stripes. TV regularization is used to preserve details, and the global low rank and directional sparsity are used to constrain stripe noise. The directional and structural characteristics of stripe noise are fully utilized to achieve a better removal effect. Moreover, we designed an alternating minimization scheme to obtain the optimal solution. Simulation and actual experimental data show that the proposed model has strong robustness and is superior to existing competitive destriping models, both subjectively and objectively. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
URL标识	查看原文
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/65584]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	X. Wu,H. Qu,L. Zheng,et al. A remote sensing image destriping model based on low-rank and directional sparse constraint[J]. Remote Sensing,2021,13(24).
APA	X. Wu,H. Qu,L. Zheng,&T. Gao and Z. Zhang.(2021).A remote sensing image destriping model based on low-rank and directional sparse constraint.Remote Sensing,13(24).
MLA	X. Wu,et al."A remote sensing image destriping model based on low-rank and directional sparse constraint".Remote Sensing 13.24(2021).