Next Article in Journal
Assessment of IMERG Precipitation Estimates over Europe
Next Article in Special Issue
An Improved Mapping with Super-Resolved Multispectral Images for Geostationary Satellites
Previous Article in Journal
Retrieval of the Fraction of Radiation Absorbed by Photosynthetic Components (FAPARgreen) for Forest Using a Triple-Source Leaf-Wood-Soil Layer Approach
Previous Article in Special Issue
Fusion of Various Band Selection Methods for Hyperspectral Imagery
Open AccessArticle

Removal of Large-Scale Stripes Via Unidirectional Multiscale Decomposition

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China
2
School of Computer, Hubei University of Technology, Wuhan 430068, China
3
Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China
4
School of Resource and Environment Sciences, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(21), 2472; https://doi.org/10.3390/rs11212472
Received: 28 August 2019 / Revised: 21 October 2019 / Accepted: 21 October 2019 / Published: 23 October 2019
(This article belongs to the Special Issue Quality Improvement of Remote Sensing Images)
Stripes are common in remote sensing imaging systems equipped with multichannel time delay integration charge-coupled devices (TDI CCDs) and have different scale characteristics depending on their causes. Large-scale stripes appearing between channels are difficult to process by most current methods. The framework of column-by-column nonuniformity correction (CCNUC) is introduced to eliminate large-scale stripes. However, the worst problem of CCNUC is the unavoidable cumulative error, which will cause an overall color cast. To eliminate large-scale stripes and suppress the cumulative error, we proposed a destriping method via unidirectional multiscale decomposition (DUMD). The striped image was decomposed by constructing a unidirectional pyramid and making difference maps layer by layer. The highest layer of the pyramid was processed by CCNUC to eliminate large-scale stripes, and multiple cumulative error suppression measures were performed to reduce overall color cast. The difference maps of the pyramid were processed by a designed filter to eliminate small-scale stripes. Experiments showed that DUMD had good destriping performance and was robust with respect to different terrains. View Full-Text
Keywords: destriping; column-by-column nonuniformity correction (CCNUC); cumulative error; unidirectional multiscale decomposition destriping; column-by-column nonuniformity correction (CCNUC); cumulative error; unidirectional multiscale decomposition
Show Figures

Graphical abstract

MDPI and ACS Style

He, L.; Wang, M.; Chang, X.; Zhang, Z.; Feng, X. Removal of Large-Scale Stripes Via Unidirectional Multiscale Decomposition. Remote Sens. 2019, 11, 2472.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop