A Robust Pansharpening Algorithm Based on Convolutional Sparse Coding for Spatial Enhancement

Pansharpening (PS) is a prominent remote sensing image fusion technique. It yields high-resolution multispectral (HRMS) images, which are imperative for the applications, such as recognition and detection. The PS methods based on conventional sparse representation induce blurring effects and are una...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 12; číslo 10; s. 4024 - 4037
Hlavní autori:	Gogineni, Rajesh, Chaturvedi, Ashvini
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.10.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Blurring Cartoon plus texture (CPT) decomposition Components Computer vision Convolutional codes convolutional sparse coding (CSC) Dictionaries Distortion Evaluation fusion models gradient strength Image acquisition Image coding Image detection Image enhancement Image processing Image reconstruction Image resolution Object recognition Pansharpening pansharpening (PS) Remote sensing sparse representation (SR) Texture
ISSN:	1939-1404, 2151-1535
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Abstract	Pansharpening (PS) is a prominent remote sensing image fusion technique. It yields high-resolution multispectral (HRMS) images, which are imperative for the applications, such as recognition and detection. The PS methods based on conventional sparse representation induce blurring effects and are unable to preserve the essential spatial details in the fused outcome. In this article, to overcome these drawbacks, a robust fusion scheme is proposed based on convolutional sparse coding (CSC). The source images are decomposed into its constituent texture and cartoon components. The sparse coefficient maps are acquired from texture components by adapting CSC. Texture components are fused using activity level measurement, whereas averaging mechanism is used to fuse the cartoon components. The HRMS image is reconstructed by combining the fused components in proportion to the gradient information. Impact of number of filters on quality metrics estimation is analyzed. Comprehensive experiments are performed on the images acquired from distinct sensors. The proposed method is evaluated in terms of visual analysis and the quantitative metrics with reduced-scale and full-scale experiments. Extensive evaluations manifest the capability of the proposed method of maintaining the balanced tradeoff and retaining the desired spatial and spectral details.
AbstractList	Pansharpening (PS) is a prominent remote sensing image fusion technique. It yields high-resolution multispectral (HRMS) images, which are imperative for the applications, such as recognition and detection. The PS methods based on conventional sparse representation induce blurring effects and are unable to preserve the essential spatial details in the fused outcome. In this article, to overcome these drawbacks, a robust fusion scheme is proposed based on convolutional sparse coding (CSC). The source images are decomposed into its constituent texture and cartoon components. The sparse coefficient maps are acquired from texture components by adapting CSC. Texture components are fused using activity level measurement, whereas averaging mechanism is used to fuse the cartoon components. The HRMS image is reconstructed by combining the fused components in proportion to the gradient information. Impact of number of filters on quality metrics estimation is analyzed. Comprehensive experiments are performed on the images acquired from distinct sensors. The proposed method is evaluated in terms of visual analysis and the quantitative metrics with reduced-scale and full-scale experiments. Extensive evaluations manifest the capability of the proposed method of maintaining the balanced tradeoff and retaining the desired spatial and spectral details.
Author	Gogineni, Rajesh Chaturvedi, Ashvini
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Cites_doi	10.1109/TIP.2010.2046605 10.1109/JSTARS.2018.2835573 10.1109/TGRS.2015.2504261 10.1109/JSTARS.2015.2507859 10.1016/S0924-2716(03)00013-3 10.1109/JSTARS.2014.2306332 10.1109/JSTARS.2017.2697445 10.1137/S1540345902416247 10.1109/JSTARS.2014.2310781 10.14358/PERS.72.5.591 10.1109/36.763274 10.1109/TGRS.2008.916211 10.1109/JSTARS.2015.2475754 10.1109/TIT.2011.2146090 10.1002/cpa.20124 10.1109/JPROC.2009.2037655 10.14358/PERS.74.2.193 10.1109/TGRS.2014.2361734 10.1109/JSTARS.2018.2849011 10.1016/j.inffus.2016.03.003 10.1109/TGRS.2012.2213604 10.1080/2150704X.2017.1415470 10.1109/LGRS.2014.2331291 10.1109/LGRS.2004.834804 10.1109/JSTARS.2014.2347072 10.1109/LGRS.2011.2177063 10.1109/TIP.2015.2495260 10.1109/ACCESS.2017.2735865 10.1016/j.ins.2017.09.010 10.1109/TGRS.2005.856106 10.1109/TGRS.2010.2067219 10.1109/LGRS.2005.845313 10.1109/CVPR.2013.57 10.1007/s10851-006-7801-6 10.1109/TSP.2006.881199 10.1109/TGRS.2012.2230332 10.1109/JSTARS.2013.2283236 10.1201/b18189 10.1109/TIM.2009.2026612 10.1109/LSP.2016.2618776 10.1109/JSTARS.2016.2546061 10.1109/LGRS.2013.2256875 10.1109/TGRS.2015.2497309 10.1109/TGRS.2006.881758
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References	ref13 ref12 ref15 ref14 ref11 ref10 wald (ref46) 1997; 63 ref17 ref16 ref19 ref18 meyer (ref39) 2001; 22 wohlberg (ref49) 2016 ref45 ref48 ref47 ref42 ref41 ref44 ref43 ref8 ref7 carper (ref3) 1990; 56 ref9 ref4 ref5 ref40 ref35 ref34 ref37 ref36 ref31 ref30 ref33 ref32 ref2 ref1 ref38 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 laben (ref6) 2000 ref29
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SubjectTerms	Algorithms Blurring Cartoon plus texture (CPT) decomposition Components Computer vision Convolutional codes convolutional sparse coding (CSC) Dictionaries Distortion Evaluation fusion models gradient strength Image acquisition Image coding Image detection Image enhancement Image processing Image reconstruction Image resolution Object recognition Pansharpening pansharpening (PS) Remote sensing sparse representation (SR) Texture
Title	A Robust Pansharpening Algorithm Based on Convolutional Sparse Coding for Spatial Enhancement
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