{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T14:49:56Z","timestamp":1770907796213,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T00:00:00Z","timestamp":1727222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This work presents two pre-processing patches to automatically correct the residual local misalignment of datasets acquired by very\/extremely high resolution (VHR\/EHR) satellite multispectral (MS) scanners, one for, e.g., GeoEye-1 and Pl\u00e9iades, featuring two separate instruments for MS and panchromatic (Pan) data, the other for WorldView-2\/3 featuring three instruments, two of which are visible and near-infra-red (VNIR) MS scanners. The misalignment arises because the two\/three instruments onboard GeoEye-1 \/ WorldView-2 (four onboard WorldView-3) share the same optics and, thus, cannot have parallel optical axes. Consequently, they image the same swath area from different positions along the orbit. Local height changes (hills, buildings, trees, etc.) originate local shifts among corresponding points in the datasets. The latter would be accurately aligned only if the digital elevation surface model were known with sufficient spatial resolution, which is hardly feasible everywhere because of the extremely high resolution, with Pan pixels of less than 0.5 m. The refined co-registration is achieved by injecting the residue of the multivariate linear regression of each scanner towards lowpass-filtered Pan. Experiments with two and three instruments show that an almost perfect alignment is achieved. MS pansharpening is also shown to greatly benefit from the improved alignment. The proposed alignment procedures are real-time, fully automated, and do not require any additional or ancillary information, but rely uniquely on the unimodality of the MS and Pan sensors.<\/jats:p>","DOI":"10.3390\/rs16193576","type":"journal-article","created":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T04:05:46Z","timestamp":1727323546000},"page":"3576","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Automatic Fine Co-Registration of Datasets from Extremely High Resolution Satellite Multispectral Scanners by Means of Injection of Residues of Multivariate Regression"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8984-938X","authenticated-orcid":false,"given":"Luciano","family":"Alparone","sequence":"first","affiliation":[{"name":"Department of Information Engineering, University of Florence, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1584-4631","authenticated-orcid":false,"given":"Alberto","family":"Arienzo","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, 50139 Florence, Italy"},{"name":"National Research Council, Institute of Methodologies for Environmental Analysis, 85050 Tito Scalo, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2332-780X","authenticated-orcid":false,"given":"Andrea","family":"Garzelli","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alparone, L., Aiazzi, B., Baronti, S., and Garzelli, A. (2015). Remote Sensing Image Fusion, CRC Press.","DOI":"10.1201\/b18189"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3966","DOI":"10.1109\/JSTARS.2019.2945188","article-title":"A novel multispectral, panchromatic and SAR data fusion for land classification","volume":"12","author":"Iervolino","year":"2019","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1109\/TGRS.2004.837328","article-title":"Information-theoretic heterogeneity measurement for SAR imagery","volume":"43","author":"Aiazzi","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/MGRS.2020.3019315","article-title":"A new benchmark based on recent advances in multispectral pansharpening: Revisiting pansharpening with classical and emerging pansharpening methods","volume":"9","author":"Vivone","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1109\/TGRS.2007.912448","article-title":"Synthesis of multispectral images to high spatial resolution: A critical review of fusion methods based on remote sensing physics","volume":"46","author":"Thomas","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.isprsjprs.2013.09.007","article-title":"Bi-cubic interpolation for shift-free pan-sharpening","volume":"86","author":"Aiazzi","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Alparone, L., Garzelli, A., and Zoppetti, C. (2023). Fusion of VNIR optical and C-band polarimetric SAR satellite data for accurate detection of temporal changes in vegetated areas. Remote Sens., 15.","DOI":"10.3390\/rs15030638"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1109\/JSTARS.2014.2304700","article-title":"SAR image classification through information-theoretic textural features, MRF segmentation, and object-oriented learning vector quantization","volume":"7","author":"Ruscino","year":"2014","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1117\/12.373263","article-title":"Wavelet and pyramid techniques for multisensor data fusion: A performance comparison varying with scale ratios","volume":"Volume 3871","author":"Serpico","year":"1999","journal-title":"Image and Signal Processing for Remote Sensing V"},{"key":"ref_10","first-page":"12","article-title":"Advantages of Laplacian pyramids over \u201d\u00e0 trous\u201d wavelet transforms for pansharpening of multispectral images","volume":"Volume 8537","author":"Bruzzone","year":"2012","journal-title":"Image and Signal Processing for Remote Sensing XVIII"},{"key":"ref_11","unstructured":"Garzelli, A., Nencini, F., Alparone, L., and Baronti, S. (2005, January 25\u201329). Multiresolution fusion of multispectral and panchromatic images through the curvelet transform. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Seoul, Republic of Korea."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1109\/JSTSP.2011.2104938","article-title":"A theoretical analysis of the effects of aliasing and misregistration on pansharpened imagery","volume":"5","author":"Baronti","year":"2011","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_13","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 data sets","volume":"55","author":"Aiazzi","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4213","DOI":"10.1109\/TIP.2015.2456415","article-title":"SIRF: Simultaneous satellite image registration and fusion in a unified framework","volume":"24","author":"Chen","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Santarelli, C., Carfagni, M., Alparone, L., Arienzo, A., and Argenti, F. (2022). Multimodal fusion of tomographic sequences of medical images: MRE spatially enhanced by MRI. Comput. Meth. Progr. Biomed., 223.","DOI":"10.1016\/j.cmpb.2022.106964"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6587","DOI":"10.1109\/TGRS.2016.2587321","article-title":"Multimodal remote sensing image registration with accuracy estimation at local and global scales","volume":"54","author":"Uss","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","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_18","doi-asserted-by":"crossref","first-page":"5039","DOI":"10.1109\/JSTARS.2017.2730221","article-title":"Improvement of a pansharpening method taking into account haze","volume":"10","author":"Li","year":"2017","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2255","DOI":"10.1109\/LGRS.2017.2761021","article-title":"Haze correction for contrast-based multispectral pansharpening","volume":"14","author":"Lolli","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6241","DOI":"10.1109\/TGRS.2013.2295819","article-title":"The importance of physical quantities for the analysis of multitemporal and multiangular optical very high spatial resolution images","volume":"52","author":"Pacifici","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1109\/JSTARS.2014.2321332","article-title":"Sequential Bayesian methods for resolution enhancement of TIR image sequences","volume":"8","author":"Addesso","year":"2015","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_22","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_23","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. Remote Sens. Lett."},{"key":"ref_24","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_25","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_26","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.inffus.2020.04.006","article-title":"Pan-GAN: An unsupervised pan-sharpening method for remote sensing image fusion","volume":"62","author":"Ma","year":"2020","journal-title":"Inform. Fusion"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.inffus.2018.09.004","article-title":"FusionGAN: A generative adversarial network for infrared and visible image fusion","volume":"48","author":"Ma","year":"2019","journal-title":"Inform. Fusion"},{"key":"ref_28","unstructured":"Bruzzone, L., and Bovolo, F. (2018). Deployment of pansharpening for correction of local misalignments between MS and Pan. Image and Signal Processing for Remote Sensing XXIV, SPIE."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Arienzo, A., Alparone, L., Aiazzi, B., and Garzelli, A. (October, January 26). Automatic fine alignment of multispectral and panchromatic images. Proceedings of the 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Waikoloa, HI, USA.","DOI":"10.1109\/IGARSS39084.2020.9324689"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lee, C., and Oh, J. (2020). Rigorous co-registration of KOMPSAT-3 multispectral and panchromatic images for pan-sharpening image fusion. Sensors, 20.","DOI":"10.3390\/s20072100"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Xie, G., Wang, M., Zhang, Z., Xiang, S., and He, L. (2021). Near real-time automatic sub-pixel registration of panchromatic and multispectral images for pan-sharpening. Remote Sens., 13.","DOI":"10.3390\/rs13183674"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Aiazzi, B., Selva, M., Arienzo, A., and Baronti, S. (2019). Influence of the system MTF on the on-board lossless compression of hyperspectral raw data. Remote Sens., 11.","DOI":"10.3390\/rs11070791"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"295950","DOI":"10.1155\/2013\/295950","article-title":"End-to-end image simulator for optical imaging systems: Equations and simulation examples","volume":"2013","author":"Coppo","year":"2013","journal-title":"Adv. Opt. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"7181","DOI":"10.1080\/01431160802238393","article-title":"Geometric accuracy assessment of the orthorectification process from very high resolution satellite imagery for Common Agricultural Policy purposes","volume":"29","author":"Aguilar","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1080\/2150704X.2014.950761","article-title":"Accurate registration of optical satellite imagery with elevation models for topographic correction","volume":"5","author":"Shepherd","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2018.06.016","article-title":"High-precision co-registration of orbiter imagery and digital elevation model constrained by both geometric and photometric information","volume":"144","author":"Xin","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Le Moigne, J., Netanyahu, N.S., and Eastman, R.D. (2011). Image Registration for Remote Sensing, Cambridge University Press.","DOI":"10.1017\/CBO9780511777684"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.rse.2014.08.015","article-title":"Motion detection using near-simultaneous satellite acquisitions","volume":"154","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1080\/01431160903527405","article-title":"An image fusion method for misaligned panchromatic and multispectral data","volume":"32","author":"Jing","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1109\/LGRS.2018.2850151","article-title":"Blind correction of local misalignments between multispectral and panchromatic images","volume":"15","author":"Aiazzi","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1109\/TGRS.2020.3000267","article-title":"Hyperspectral sharpening approaches using satellite multiplatform data","volume":"59","author":"Restaino","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","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_43","doi-asserted-by":"crossref","first-page":"1308","DOI":"10.3390\/rs10081308","article-title":"Multispectral pansharpening with radiative transfer-based detail-injection modeling for preserving changes in vegetation cover","volume":"10","author":"Garzelli","year":"2018","journal-title":"Remote Sens."},{"key":"ref_44","unstructured":"Updike, T., and Comp, C. (2010). Radiometric Use of WorldView-2 Imagery, DigitalGlobe. Technical report."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Vivone, G., Alparone, L., Garzelli, A., and Lolli, S. (2019). Fast reproducible pansharpening based on instrument and acquisition modeling: AWLP revisited. Remote Sens., 11.","DOI":"10.3390\/rs11192315"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3418","DOI":"10.1109\/TIP.2018.2819501","article-title":"Full scale regression-based injection coefficients for panchromatic sharpening","volume":"27","author":"Vivone","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/MGRS.2022.3170092","article-title":"Full-resolution quality assessment of pansharpening: Theoretical and hands-on approaches","volume":"10","author":"Arienzo","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_48","first-page":"237","article-title":"Assessment of pyramid-based multisensor image data fusion","volume":"Volume 3500","author":"Serpico","year":"1998","journal-title":"Image and Signal Processing for Remote Sensing IV"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1109\/TGRS.2015.2476513","article-title":"Quantitative quality evaluation of pansharpened imagery: Consistency versus synthesis","volume":"54","author":"Palsson","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","first-page":"1273302","article-title":"Full-scale assessment of pansharpening: Why literature indexes may give contradictory results and how to avoid such an inconvenience","volume":"Volume 12733","author":"Bruzzone","year":"2023","journal-title":"Image and Signal Processing for Remote Sensing XXIX"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Alparone, L., Garzelli, A., and Vivone, G. (2018, January 22\u201327). Spatial consistency for full-scale assessment of pansharpening. Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518869"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Arienzo, A., Aiazzi, B., Alparone, L., and Garzelli, A. (2021). Reproducibility of pansharpening methods and quality indexes versus data formats. Remote Sens., 13.","DOI":"10.3390\/rs13214399"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Arienzo, A., Alparone, L., Garzelli, A., and Lolli, S. (2022). Advantages of nonlinear intensity components for contrast-based multispectral pansharpening. Remote Sens., 14.","DOI":"10.3390\/rs14143301"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"8862","DOI":"10.1080\/01431161.2020.1788744","article-title":"The effects of misregistration between hyperspectral and panchromatic images on linear spectral unmixing","volume":"41","author":"Cheng","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"201199","DOI":"10.1109\/ACCESS.2020.3035802","article-title":"UPSNet: Unsupervised pan-sharpening network with registration learning between panchromatic and multi-spectral images","volume":"8","author":"Seo","year":"2020","journal-title":"IEEE Access"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"5403814","DOI":"10.1109\/TGRS.2024.3378158","article-title":"Deep spectral blending network for color bleeding reduction in PAN-sharpening images","volume":"62","author":"Kim","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/19\/3576\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:03:06Z","timestamp":1760112186000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/19\/3576"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,25]]},"references-count":56,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["rs16193576"],"URL":"https:\/\/doi.org\/10.3390\/rs16193576","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,25]]}}}