A NSST Pansharpening method based on directional neighborhood correlation and tree structure matching
In this paper, we propose a multispectral (MS) remote sensing image pansharpening method based on non-subsampled shearlet transform (NSST). By analyzing the NSST high-frequency coefficients correlation of several datasets which are fromWorldView-2 (WV2) and Quick-Bird (QB), we verified that the high...
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| Veröffentlicht in: | Multimedia tools and applications 2019-09, Vol.78 (18), p.26787-26806 |
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| creator | Wang, Xianghai Tao, Jingzhe Shen, Yutong Bai, Shifu Song, Chuanming |
| description | In this paper, we propose a multispectral (MS) remote sensing image pansharpening method based on non-subsampled shearlet transform (NSST). By analyzing the NSST high-frequency coefficients correlation of several datasets which are fromWorldView-2 (WV2) and Quick-Bird (QB), we verified that the high-frequency coefficients based on NSST have strong directional neighborhood correlation within the same sub-band and parent-children correlation between sub-bands in the same direction. In order to combine these two kinds of correlations, we design a type of weighted directional neighborhood templates which can be used for any number of direction sub-bands to depict the direction correlation, and use the tree structure to model the correlation between parent-children coefficients. Experiments show that the proposed method in this paper can provide a fused MS image with high spatial resolution, which can provide convenience for subsequent applications such as classification and target recognition. |
| doi_str_mv | 10.1007/s11042-019-07841-5 |
| format | Article |
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By analyzing the NSST high-frequency coefficients correlation of several datasets which are fromWorldView-2 (WV2) and Quick-Bird (QB), we verified that the high-frequency coefficients based on NSST have strong directional neighborhood correlation within the same sub-band and parent-children correlation between sub-bands in the same direction. In order to combine these two kinds of correlations, we design a type of weighted directional neighborhood templates which can be used for any number of direction sub-bands to depict the direction correlation, and use the tree structure to model the correlation between parent-children coefficients. Experiments show that the proposed method in this paper can provide a fused MS image with high spatial resolution, which can provide convenience for subsequent applications such as classification and target recognition.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-019-07841-5</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Banded structure ; Coefficients ; Computer Communication Networks ; Computer Science ; Correlation analysis ; Data Structures and Information Theory ; Multimedia Information Systems ; Neighborhoods ; Remote sensing ; Spatial resolution ; Special Purpose and Application-Based Systems ; Target recognition</subject><ispartof>Multimedia tools and applications, 2019-09, Vol.78 (18), p.26787-26806</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2019</rights><rights>Multimedia Tools and Applications is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-af132994f2b681a69119c22f2b4cc38bd043582027ff0c186d59a9896e265ff3</citedby><cites>FETCH-LOGICAL-c319t-af132994f2b681a69119c22f2b4cc38bd043582027ff0c186d59a9896e265ff3</cites><orcidid>0000-0002-7600-9939</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11042-019-07841-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-019-07841-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Wang, Xianghai</creatorcontrib><creatorcontrib>Tao, Jingzhe</creatorcontrib><creatorcontrib>Shen, Yutong</creatorcontrib><creatorcontrib>Bai, Shifu</creatorcontrib><creatorcontrib>Song, Chuanming</creatorcontrib><title>A NSST Pansharpening method based on directional neighborhood correlation and tree structure matching</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>In this paper, we propose a multispectral (MS) remote sensing image pansharpening method based on non-subsampled shearlet transform (NSST). 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By analyzing the NSST high-frequency coefficients correlation of several datasets which are fromWorldView-2 (WV2) and Quick-Bird (QB), we verified that the high-frequency coefficients based on NSST have strong directional neighborhood correlation within the same sub-band and parent-children correlation between sub-bands in the same direction. In order to combine these two kinds of correlations, we design a type of weighted directional neighborhood templates which can be used for any number of direction sub-bands to depict the direction correlation, and use the tree structure to model the correlation between parent-children coefficients. 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| subjects | Banded structure Coefficients Computer Communication Networks Computer Science Correlation analysis Data Structures and Information Theory Multimedia Information Systems Neighborhoods Remote sensing Spatial resolution Special Purpose and Application-Based Systems Target recognition |
| title | A NSST Pansharpening method based on directional neighborhood correlation and tree structure matching |
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