{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T18:50:00Z","timestamp":1772736600175,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,11,24]],"date-time":"2019-11-24T00:00:00Z","timestamp":1574553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In recent years, many techniques of fusion of multi-sensors satellite images have been developed. This article focuses on examining and improvement the usability of pansharpened images for object detection, especially when fusing data with a high GSD ratio. A methodology to improve an interpretative ability of pansharpening results is based on pre-processing of the panchromatic image using Logarithmic-Laplace filtration. The proposed approach was used to examine several different pansharpening methods and data sets with different spatial resolution ratios, i.e., from 1:4 to 1:60. The obtained results showed that the proposed approach significantly improves an object detection of fused images, especially for imagery data with a high-resolution ratio. The interpretative ability was assessed using qualitative method (based on image segmentation) and quantitative method (using an indicator based on the Speeded Up Robust Features (SURF) detector). In the case of combining data acquired with the same sensor the interpretative potential had improved by a dozen or so per cent. However, for data with a high resolution ratio, the improvement was several dozen, or even several hundred per cents, in the case of images blurred after pansharpening by the classic method (with original panchromatic image). Image segmentation showed that it is possible to recognize narrow objects that were originally blurred and difficult to identify. In addition, for panchromatic images acquired by WorldView-2, the proposed approach improved not only object detection but also the spectral quality of the fused image.<\/jats:p>","DOI":"10.3390\/s19235146","type":"journal-article","created":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T03:10:00Z","timestamp":1574651400000},"page":"5146","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Pre-Processing of Panchromatic Images to Improve Object Detection in Pansharpened Images"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9291-8163","authenticated-orcid":false,"given":"Aleksandra","family":"Sekrecka","sequence":"first","affiliation":[{"name":"Department of Remote Sensing, Photogrammetry and Imagery Intelligence, Institute of Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0684-3717","authenticated-orcid":false,"given":"Michal","family":"Kedzierski","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Photogrammetry and Imagery Intelligence, Institute of Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6192-3894","authenticated-orcid":false,"given":"Damian","family":"Wierzbicki","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Photogrammetry and Imagery Intelligence, Institute of Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zheng, Y. (2011). Image Fusion for Remote Sensing Applications. Image Fusion and Its Applications, InTech.","DOI":"10.5772\/691"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Su, W., Sun, Z., Chen, W.-H., Zhang, X., Yao, C., Wu, J., Huang, J., and Zhu, D. (2019). Joint Retrieval of Growing Season Corn Canopy LAI and Leaf Chlorophyll Content by Fusing Sentinel-2 and MODIS Images. Remote Sens., 11.","DOI":"10.3390\/rs11202409"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3604","DOI":"10.1016\/j.jas.2013.04.013","article-title":"Combined application of pansharpening and enhancement methods to improve archaeological cropmark visibility and identification in QuickBird imagery: Two case studies from Apulia, Southern Italy","volume":"40","author":"Noviello","year":"2013","journal-title":"J. Archaeol. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1080\/19479830903562041","article-title":"Fusing high-resolution SAR and optical imagery for improved urban land cover study and classification","volume":"1","author":"Amarsaikhan","year":"2010","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ma, X., Li, C., Tong, X., and Liu, S. (2019). A New Fusion Approach for Extracting Urban Built-up Areas from Multisource Remotely Sensed Data. Remote Sens., 11.","DOI":"10.3390\/rs11212516"},{"key":"ref_6","unstructured":"Orych, A. (September, January 30). Review of methods for determining the spatial resolution of UAVsensors. Proceedings of the International Conference on Unmanned Aerial Vehicles in Geomatics, Toronto, ON, Canada."},{"key":"ref_7","unstructured":"Madden, M. (2009). High Resolution Image Data and GIS. ASPRS Manual of GIS, American Society for Photogrammetry and Remote Sensing."},{"key":"ref_8","unstructured":"Jolliffe, I. (2002). Principal Component Analysis, John Wiley & Sons Ltd."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Maurer, T. (2013, January 21\u201324). How to pan-sharpen images using the Gram-Schmidt pan-sharpen method-a recipe. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Hannover, Germany.","DOI":"10.5194\/isprsarchives-XL-1-W1-239-2013"},{"key":"ref_10","unstructured":"Craig, A.L., Bernard, V.B., and Inventor Eastman Kodak Co. Assigne (1998). Process for Enhancing the Spatial Resolution of Multispectral Imagery Using Pan-Sharpening. (09,069,232), U.S. Patent."},{"key":"ref_11","unstructured":"Al-Wassai, F.A., Kalyankar, N.V., and Al-Zuky, A.A. (2011). The IHS transformations based image fusion. arXiv."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1109\/LGRS.2004.834804","article-title":"A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery","volume":"1","author":"Tu","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"116201","DOI":"10.1117\/1.2124871","article-title":"Adjustable intensity-hue-saturation and Brovey transform fusion technique for IKONOS\/QuickBird imagery","volume":"44","author":"Tu","year":"2005","journal-title":"Opt. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.14358\/PERS.74.9.1107","article-title":"Optimizing the high-pass filter addition technique for image fusion","volume":"74","author":"Gangkofner","year":"2008","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1016\/j.patcog.2004.03.010","article-title":"A wavelet-based image fusion tutorial","volume":"37","author":"Pajares","year":"2004","journal-title":"Pattern Recognit."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.inffus.2004.06.009","article-title":"An IHS an wavelet integrated approach to improve pansharpening visual quality of natural colour IKONOS and QuickBird images","volume":"6","author":"Zhang","year":"2005","journal-title":"Inf. Fusion"},{"key":"ref_17","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_18","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":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TGRS.2014.2361734","article-title":"A critical comparison among pansharpening algorithms","volume":"53","author":"Vivone","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2295","DOI":"10.1109\/LGRS.2017.2762427","article-title":"Image fusion of spectrally nonoverlapping imagery using SPCA and MTF-based filters","volume":"14","author":"Kim","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_21","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":"2010","journal-title":"IEEE Trans. Geosci. 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":"6828","DOI":"10.3390\/rs70606828","article-title":"A new look at image fusion methods from a Bayesian perspective","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Qu, J., Lei, J., Li, Y., Dong, W., Zeng, Z., and Chen, D. (2018). Structure Tensor-Based Algorithm for Hyperspectral and Panchromatic Images Fusion. Remote Sens., 10.","DOI":"10.3390\/rs10030373"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Choi, J., Park, H., and Seo, D. (2019). Pansharpening Using Guided Filtering to Improve the Spatial Clarity of VHR Satellite Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11060633"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Yang, J., Fu, X., Hu, Y., Huang, Y., Ding, X., and Paisley, J. (2017, January 22\u201329). PanNet: A deep network architecture for pan-sharpening. Proceedings of the IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.193"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Li, Z., and Cheng, C. (2019). A CNN-Based Pan-Sharpening Method for Integrating Panchromatic and Multispectral Images Using Landsat 8. Remote Sens., 11.","DOI":"10.3390\/rs11222606"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hu, J., He, Z., and Wu, J. (2019). Deep Self-Learning Network for Adaptive Pansharpening. Remote Sens., 11.","DOI":"10.3390\/rs11202395"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Fryskowska, A., Wojtkowska, M., Delis, P., and Grochala, A. (2016, January 12\u201319). Some Aspects of Satellite Imagery Integration from EROS B and LANDSAT 8. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Prague, Czech Republic.","DOI":"10.5194\/isprs-archives-XLI-B7-647-2016"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Grochala, A., and Kedzierski, M. (2017). A Method of Panchromatic Image Modification for Satellite Imagery Data Fusion. Remote Sens., 9.","DOI":"10.3390\/rs9060639"},{"key":"ref_31","first-page":"104211Z","article-title":"The Fusion of Satellite and UAV Data: Simulation of High Spatial Resolution Band","volume":"Volume 10421","author":"Jenerowicz","year":"2017","journal-title":"Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Sekrecka, A., and Kedzierski, M. (2018). Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details. Sensors, 18.","DOI":"10.3390\/s18124418"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zhao, J., Zhou, C., Huang, L., Yang, X., Xu, B., and Liang, D. (2018). Fusion of Unmanned Aerial Vehicle Panchromatic and Hyperspectral Images Combining Joint Skewness-Kurtosis Figures and a Non-Subsampled Contourlet Transform. Sensors, 18.","DOI":"10.3390\/s18103467"},{"key":"ref_34","first-page":"697","article-title":"A computational approach to edge detection","volume":"6","author":"Canny","year":"1987","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_35","unstructured":"(2019, July 06). DIGITAL GLOBE. Available online: https:\/\/www.digitalglobe.com\/products\/satellite-imagery."},{"key":"ref_36","unstructured":"(2019, July 06). NASA, Available online: http:\/\/landsat.gsfc.nasa.gov."},{"key":"ref_37","first-page":"1159","article-title":"Image Denoising based on Gaussian\/Bilateral Filter and its Method Noise Thresholding","volume":"7","year":"2012","journal-title":"Signal Image Video Process"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2324","DOI":"10.1109\/TIP.2008.2006658","article-title":"Multiresolution bilateral filtering for image denoising","volume":"17","author":"Zhang","year":"2008","journal-title":"IEEE Trans. Image Process."},{"key":"ref_39","unstructured":"G\u0142owienka, E. (2015). GIS and Remote Sensing in Environmental Monitoring, Rzeszow School of Engineering and Economics, Neiko Print & Publishing."},{"key":"ref_40","unstructured":"Zhou, H., Wu, J., and Zhang, J. (2010). Digital Image Processing: Part II, Bookboon."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1080\/014311698215973","article-title":"A wavelet transform method to merge Landsat TM and SPOT panchromatic data","volume":"19","author":"Zhou","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., and Van Gool, L. (2006). Surf: Speeded up Robust Features. European Conference on Computer Vision, Springer.","DOI":"10.1007\/11744023_32"},{"key":"ref_43","first-page":"355","article-title":"GPU accelerating speeded-up robust features","volume":"8","author":"Terriberry","year":"2008","journal-title":"Proc. 3DPVT"},{"key":"ref_44","first-page":"411","article-title":"Quality measures for image segmentation using generated images","volume":"2579","author":"Schouten","year":"1995","journal-title":"In Image Signal Process. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Wang, Z., Bovik, A.C., and Lu, L. (2002, January 13\u201317). Why is image quality assessment so difficult?. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Orlando, FL, USA.","DOI":"10.1109\/ICASSP.2002.5745362"},{"key":"ref_46","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_47","first-page":"49","article-title":"Fusion of High Spatial and Spectral Resolution Images: The ARSIS Concept and its Implementation","volume":"66","author":"Ranchin","year":"2000","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_48","unstructured":"Wald, L. (2019, October 03). Quality of High Resolution Synthesised Images: Is There a Simple Criterion?. Available online: https:\/\/hal.archives-ouvertes.fr\/hal-00395027\/document."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/S0924-2716(03)00013-3","article-title":"Image fusion\u2014The ARSIS concept and some successful implementation schemes","volume":"58","author":"Ranchin","year":"2003","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","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 Pansharpened Images","volume":"15","author":"Selva","year":"2018","journal-title":"IEEE Geosc. Remote Sens. Lett."},{"key":"ref_51","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_52","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1109\/LGRS.2012.2210857","article-title":"Hybrid pansharpening algorithm for high spatial resolution satellite imagery to improve spatial quality","volume":"10","author":"Choi","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"367","DOI":"10.5589\/m08-041","article-title":"A directed search algorithm for setting the spectral\u2013spatial quality trade-off of fused images by the wavelet \u00e0 trous method","volume":"34","author":"Gonzalo","year":"2008","journal-title":"Can. J. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1109\/LGRS.2012.2207944","article-title":"Evaluation of spatial and spectral effectiveness of pixel-level fusion techniques","volume":"10","author":"Marcello","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Gillmann, C., Arbelaez, P., Hernandez, J., Hagen, H., and Wischgoll, T. (2018). An Uncertainty-Aware Visual System for Image Pre-Processing. J. Imaging, 4.","DOI":"10.3390\/jimaging4090109"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5146\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:37:09Z","timestamp":1760189829000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5146"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,24]]},"references-count":55,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19235146"],"URL":"https:\/\/doi.org\/10.3390\/s19235146","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,24]]}}}