{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T17:24:04Z","timestamp":1792689844225,"version":"4.5.0"},"reference-count":70,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,25]],"date-time":"2019-03-25T00:00:00Z","timestamp":1553472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61877049, 61572393, 11671317, and 11601415"],"award-info":[{"award-number":["61877049, 61572393, 11671317, and 11601415"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Pansharpening is the process of integrating a high spatial resolution panchromatic image with a low spatial resolution multispectral image to obtain a multispectral image with high spatial and spectral resolution. Over the last decade, several algorithms have been developed for pansharpening. In this paper, a technique, called enhanced back-projection (EBP), is introduced and applied as postprocessing on the pansharpening. The proposed EBP first enhances the spatial details of the pansharpening results by histogram matching and high-pass modulation, followed by a back-projection process, which takes into account the modulation transfer function (MTF) of the satellite sensor such that the pansharpening results obey the consistency property. The EBP is validated on four datasets acquired by different satellites and several commonly used pansharpening methods. The pansharpening results achieve substantial improvements by this postprocessing technique, which is widely applicable and requires no modification of existing pansharpening methods.<\/jats:p>","DOI":"10.3390\/rs11060712","type":"journal-article","created":{"date-parts":[[2019,3,25]],"date-time":"2019-03-25T06:56:52Z","timestamp":1553497012000},"page":"712","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Enhanced Back-Projection as Postprocessing for Pansharpening"],"prefix":"10.3390","volume":"11","author":[{"given":"Junmin","family":"Liu","sequence":"first","affiliation":[{"name":"School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongrong","family":"Fei","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huirong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer Application, Shangluo University, Shangluo 726000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiangshe","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,25]]},"reference":[{"key":"ref_1","first-page":"3","article-title":"Spectral imaging for remote sensing","volume":"14","author":"Shaw","year":"2003","journal-title":"Linc. Lab. J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/LGRS.2009.2029248","article-title":"Analysis of the effects of pansharpening in change detection on VHR image","volume":"7","author":"Bovolo","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.geoderma.2018.01.017","article-title":"Effects of image pansharpening on soil total nitrogen prediction models in South India","volume":"320","author":"Xu","year":"2018","journal-title":"Geoderma"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.inffus.2004.06.006","article-title":"Thematic and statistical evaluations of five panchromatic\/multispectral fusion methods on simulated PLEIADES-HR images","volume":"6","author":"Flouzat","year":"2005","journal-title":"Inf. Fusion"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3012","DOI":"10.1109\/TGRS.2007.904923","article-title":"Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data-fusion contest","volume":"45","author":"Alparone","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TGRS.2014.2361734","article-title":"A critical comparison among pansharpenig algorithms","volume":"53","author":"Vivone","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1109\/TGRS.2016.2606324","article-title":"Sensitivity of pansharpening methods to temporal and instrumental changes between multispectral and panchromatic datasets","volume":"55","author":"Aiazzi","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/S1566-2535(01)00036-7","article-title":"A new look at IHS-like image fusion methods","volume":"2","author":"Tu","year":"2001","journal-title":"Inf. Fusion"},{"key":"ref_9","first-page":"339","article-title":"Extracting spectral contrast in Landsat thematic mapper image data using selective principal component analysis","volume":"55","author":"Chavez","year":"1989","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_10","unstructured":"Laben, C.A., and Brower, B.V. (2000). Process for Enhancing the Spatial Resolution of Multispectral Imagery Using Pan-Sharpening. (6011875), U.S. Patent."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3230","DOI":"10.1109\/TGRS.2007.901007","article-title":"Improving component substitution pansharpening through multivariate regression of MS+Pan data","volume":"45","author":"Aiazzi","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1109\/TGRS.2010.2051674","article-title":"A new adaptive component-substitution-based satellite image fusion by using partial replacement","volume":"49","author":"Choi","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1109\/TGRS.2007.907604","article-title":"Optimal MMSE pan sharpening of very high resolution multispectral images","volume":"46","author":"Garzelli","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5088","DOI":"10.1109\/TGRS.2013.2286827","article-title":"Pansharpening with matting model","volume":"52","author":"Kang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1080\/01431161.2016.1163749","article-title":"Pan-sharpening using a guided filter","volume":"37","author":"Liu","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1109\/LGRS.2013.2284282","article-title":"An improved adaptive intensity-hue-saturation method for the fusion of remote sensing images","volume":"11","author":"Leung","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","unstructured":"Schowengerdt, R.A. (1997). Remote Sensing: Models and Methods for Image Processing, Academic. [2nd ed.]."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3461","DOI":"10.1080\/014311600750037499","article-title":"Smoothing filter based intensity modulation: A spectral preserve image fusion technique for improving spatial details","volume":"21","author":"Liu","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"591","DOI":"10.14358\/PERS.72.5.591","article-title":"MTF-tailored multiscale fusion of high-resolution MS and Pan imagery","volume":"72","author":"Aiazzi","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2882","DOI":"10.1109\/TIP.2016.2556944","article-title":"Fusion of multispectral and panchromatic images based on morphological operators","volume":"25","author":"Restaino","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/TGRS.2009.2028613","article-title":"Fast and efficient panchromatic sharpening","volume":"48","author":"Lee","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"9728","DOI":"10.1109\/ACCESS.2017.2710226","article-title":"Locally linear detail injection for pansharpening","volume":"5","author":"Liu","year":"2017","journal-title":"IEEE Access"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1109\/36.763274","article-title":"Multiresolution-based image fusion with additive wavelent decomposition","volume":"37","author":"Otazu","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2984","DOI":"10.1109\/JSTARS.2015.2420582","article-title":"Processing of multiresolution thermal hyperspectral and digital color data: Outcome of the 2014 IEEE GRSS Data Fusion Contest","volume":"8","author":"Liao","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1109\/TGRS.2008.916211","article-title":"An efficient pan-sharpening method via a combined adaptive PCA approach and contourlets","volume":"46","author":"Shah","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","unstructured":"Smith, W.J. (2008). Chapter 15.8 The Modulation Transfer Function. Modern Optical Engineering, McGraw-Hill Education. [4th ed.]."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1109\/LGRS.2008.2012003","article-title":"A comparison between global and context-adaptive pansharpening of multispectral images","volume":"6","author":"Aiazzi","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_28","first-page":"228","article-title":"Fusion of multispectral and panchromatic images using a restoration-based method","volume":"46","author":"Li","year":"2009","journal-title":"IEEE Trans. Geosci. Remot Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/LGRS.2013.2257669","article-title":"A new pansharpening algorithm based on total variation","volume":"11","author":"Palsson","year":"2014","journal-title":"IEEE Geosci. Remot Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4160","DOI":"10.1109\/TIP.2014.2333661","article-title":"A new pansharpening method based on spatial and spectral sparsity priors","volume":"23","author":"He","year":"2014","journal-title":"IEEE Trans. Image Process."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1109\/TGRS.2010.2067219","article-title":"A new pansharpening method using a compressed sensing technique","volume":"49","author":"Li","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2827","DOI":"10.1109\/TGRS.2012.2213604","article-title":"A sparse image fusion algorithm with application to pan-sharpening","volume":"51","author":"Zhu","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1792","DOI":"10.1109\/JSTARS.2013.2283236","article-title":"Two-step sparse coding for the pan-sharpening of remote sensing images","volume":"7","author":"Jiang","year":"2014","journal-title":"IEEE Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4779","DOI":"10.1109\/TGRS.2012.2230332","article-title":"Remote sensing image fusion via sparse representations over learned dictionaries","volume":"51","author":"Li","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1109\/LGRS.2014.2331291","article-title":"A pansharpening method based on the sparse representation of injected details","volume":"12","author":"Vicinanza","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2664","DOI":"10.1109\/TGRS.2015.2504261","article-title":"Exploiting joint sparsity for pansharpening: The j-sparsefi algorithm","volume":"54","author":"Zhu","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1109\/TGRS.2008.917131","article-title":"Bayesian data fusion for adaptable image pansharpening","volume":"46","author":"Fasbender","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MGRS.2017.2762307","article-title":"Deep learning in remote sensing: A comprehensive review and list of resources","volume":"5","author":"Zhu","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MGRS.2016.2540798","article-title":"Deep learning for remote sensing data: A technical tutorial on the state of the art","volume":"4","author":"Zhang","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1109\/LGRS.2014.2376034","article-title":"A new pan-sharpening method with deep neural networks","volume":"12","author":"Huang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Masi, G., Cozzolino, D., Verdoliva, L., and Scarpa, G. (2016). Pansharpening by convolutional neural networks. Remote Sens., 8.","DOI":"10.3390\/rs8070594"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1795","DOI":"10.1109\/LGRS.2017.2736020","article-title":"Boosting the accuracy of multispectral image pansharpening by learning a deep residual network","volume":"14","author":"Wei","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/MGRS.2015.2440094","article-title":"Hyperspectral pansharpening: A review","volume":"3","author":"Loncan","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1109\/LGRS.2017.2677087","article-title":"Band assignment approaches for hyperspectral sharpening","volume":"14","author":"Picone","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"4682","DOI":"10.1109\/TGRS.2017.2697943","article-title":"Intersensor statistical matching for pansharpening: Theoretical issues and practical solutions","volume":"55","author":"Alparone","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Xie, B., Zhang, H.K., and Huang, B. (2017). Revealing implicit assumptions of the component substitution pansharpening methods. Remote Sens., 9.","DOI":"10.3390\/rs9050443"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1109\/LGRS.2013.2281996","article-title":"Contrast and error-based fusion schemes for multispectral image pansharpening","volume":"11","author":"Vivone","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1109\/TGRS.2017.2757508","article-title":"A regression-based high-pass modulation pansharpening approach","volume":"56","author":"Vivone","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","first-page":"691","article-title":"Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images","volume":"63","author":"Wald","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1006\/jvci.1993.1030","article-title":"Motion analysis for image enhancement: resolution, occlusion and transparency","volume":"4","author":"Irani","year":"1993","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Haris, M., Shakhnarovich, G., and Ukita, N. (arXiv, 2018). Deep back-projection networks for superresolution, arXiv.","DOI":"10.1109\/CVPR.2018.00179"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Timofte, R., Rothe, R., and Van Gool, L. (2016, January 27\u201330). Seven ways to improve example-based single image super resolution. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.206"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1109\/TGRS.2005.846874","article-title":"A comparative analysis of image fusion methods","volume":"43","author":"Wang","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3124","DOI":"10.1109\/TGRS.2014.2369056","article-title":"MTF-adjust pansharpening approach based on coupled multiresolution decompositions","volume":"53","author":"Kallel","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1007\/s11045-016-0421-4","article-title":"High spectral quality pansharpening approach based on MTF-matched filter banks","volume":"27","author":"Hallabia","year":"2016","journal-title":"Multidimens. Syst. Signal Process."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Dai, S., Han, M., Wu, Y., and Gong, Y. (2007, January 2\u20135). Bilateral back-projection for single image super resolution. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo (ICME\u201907), Beijing, China.","DOI":"10.1109\/ICME.2007.4284831"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/1049-9652(91)90045-L","article-title":"Improving resolutin by image registration","volume":"53","author":"Irani","year":"1991","journal-title":"CVGIP Graph. Models Image Process."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.neucom.2016.11.049","article-title":"Iterative projection reconstruction for fast and efficient image upsampling","volume":"226","author":"Zhao","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11760-016-0880-y","article-title":"First-order derivative-based super-resolution","volume":"11","author":"Haris","year":"2017","journal-title":"Signal Image Video Process."},{"key":"ref_60","unstructured":"Dong, W., Zhang, L., Shi, G., and Wu, X. (2009, January 7\u201310). Nonlocal back-projection for adaptive image enlargement. Proceedings of the 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, Egypt."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2861","DOI":"10.1109\/TIP.2010.2050625","article-title":"Image super-resolution via sparse representation","volume":"19","author":"Yang","year":"2010","journal-title":"IEEE Trans. Image Process."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1109\/LGRS.2017.2777916","article-title":"On the use of the expanded image in quality assessment of pansharpening images","volume":"15","author":"Selva","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1606","DOI":"10.1109\/LGRS.2016.2597271","article-title":"Nonlinear IHS: A promising method for pan-sharpening","volume":"13","author":"Ghahremani","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"193","DOI":"10.14358\/PERS.74.2.193","article-title":"Multispectral and panchromatic data fusion assessment without reference","volume":"74","author":"Alparone","year":"2008","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_65","first-page":"1067","article-title":"Multiresolution wavelet decomposition image merger of Landsat Thematic Mapper and SPOT panchromatic data","volume":"62","author":"Yocky","year":"1996","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_66","unstructured":"Wald, L. (2000, January 26\u201328). Quality of high resolution synthesised images: Is there a simple criterion?. Proceedings of the Third Conferences on Fusion of Earth Data: Merging Point Measurements, Raster Maps and Remotely Sensed Images, Sophia Antipolis, France."},{"key":"ref_67","unstructured":"Yuhas, R., and Boardman, J. (1992, January 1\u20135). Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (sam) algorithm. Proceedings of the 3rd Annual JPL Airborne Geoscience Workshop, JPL Publication, Pasadena, CA, USA."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1109\/LGRS.2004.836784","article-title":"A global quality measurement of pan-sharpened multispectral imagery","volume":"1","author":"Alparone","year":"2004","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1109\/LGRS.2009.2022650","article-title":"Hypercomplex quality assessment of multi\/hyperspectral images","volume":"6","author":"Garzelli","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1109\/97.995823","article-title":"A universal image quality index","volume":"9","author":"Wang","year":"2002","journal-title":"IEEE Signal Process. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/6\/712\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:40:23Z","timestamp":1760186423000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/6\/712"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,25]]},"references-count":70,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["rs11060712"],"URL":"https:\/\/doi.org\/10.3390\/rs11060712","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,25]]}}}