{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:46:59Z","timestamp":1760143619587,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T00:00:00Z","timestamp":1708560000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003213","name":"Beijing Municipal Education Commission","doi-asserted-by":"publisher","award":["KZ202210028045"],"award-info":[{"award-number":["KZ202210028045"]}],"id":[{"id":"10.13039\/501100003213","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Beijing Satellite 3 is a high-performance optical remote sensing satellite with a spatial resolution of 0.3\u20130.5 m. It can provide timely and independent ultra-high-resolution spatial big data and comprehensive spatial information application services. At present, there is no relevant research on the fusion method of BJ-3A satellite images. In many applications, high-resolution panchromatic images alone are insufficient. Therefore, it is necessary to fuse them with multispectral images that contain spectral color information. Currently, there is a lack of research on the fusion method of BJ-3A satellite images. This article explores six traditional pixel-level fusion methods (HPF, HCS, wavelet, modified-IHS, PC, and Brovey) for fusing the panchromatic image and multispectral image of the BJ-3A satellite. The fusion results were analyzed qualitatively from two aspects: spatial detail enhancement capability and spectral fidelity. Five indicators, namely mean, standard deviation, entropy, correlation coefficient, and average gradient, were used for quantitative analysis. Finally, the fusion results were comprehensively evaluated from three aspects: spectral curves of ground objects, absolute error figure, and object-oriented classification effects. The findings of the research suggest that the fusion method known as HPF is the optimum and appropriate technique for fusing panchromatic and multispectral images obtained from BJ-3A. These results can be utilized as a guide for the implementation of BJ-3A panchromatic and multispectral data fusion in real-world scenarios.<\/jats:p>","DOI":"10.3390\/s24051410","type":"journal-article","created":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T08:34:35Z","timestamp":1708590875000},"page":"1410","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Assessing the Efficacy of Pixel-Level Fusion Techniques for Ultra-High-Resolution Imagery: A Case Study of BJ-3A"],"prefix":"10.3390","volume":"24","author":[{"given":"Yueyang","family":"Wang","sequence":"first","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"}]},{"given":"Zhihui","family":"Mao","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"},{"name":"Resource and Environmental Research Center, Chinese Academy of Fishery Sciences, Beijing 100141, China"}]},{"given":"Zhining","family":"Xin","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"}]},{"given":"Xinyi","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"}]},{"given":"Zhangmai","family":"Li","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"}]},{"given":"Yakun","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4574-7381","authenticated-orcid":false,"given":"Lei","family":"Deng","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/S1006-1266(08)60289-8","article-title":"Application of Remote-Sensing-Image Fusion to the Monitoring of Mining Induced Subsidence","volume":"18","author":"Li","year":"2008","journal-title":"J. China Univ. Min. Technol."},{"key":"ref_2","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":"Guo","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"93","DOI":"10.2747\/1548-1603.44.2.93","article-title":"Image Fusion Using the Ehlers Spectral Characteristics Preservation Algorithm","volume":"44","author":"Klonus","year":"2007","journal-title":"GIScience Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"012051","DOI":"10.1088\/1742-6596\/2419\/1\/012051","article-title":"Fusion of Remote Sensing Images Based on Multi-Resolution Analysis","volume":"2419","author":"Qi","year":"2023","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.inffus.2022.12.026","article-title":"Panchromatic and Multispectral Image Fusion for Remote Sensing and Earth Observation: Concepts, Taxonomy, Literature Review, Evaluation Methodologies and Challenges Ahead","volume":"93","author":"Zhang","year":"2023","journal-title":"Inf. Fusion"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1186\/1687-6180-2011-79","article-title":"A Survey of Classical Methods and New Trends in Pansharpening of Multispectral Images","volume":"2011","author":"Amro","year":"2011","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_7","unstructured":"Tang, Y. (2018). Research on Fusion Method of High-Resolution Remote Sensing Images Based on Pixel Level. [Master\u2019s Thesis, Donghua University of Science and Technology]."},{"key":"ref_8","unstructured":"Wu, M., and Gao, L. (2022). Comparison of domestic satellite remote sensing image fusion methods. Bull. Surv. Mapp., 150\u2013155."},{"key":"ref_9","first-page":"83","article-title":"Comparison and analysis of domestic high-resolution remote sensing image fusion methods","volume":"36","author":"Xing","year":"2016","journal-title":"J. Cent. South Univ. For. Technol."},{"key":"ref_10","first-page":"178","article-title":"Research on image fusion and quality evaluation methods of Gaofen-1 remote sensing satellite","volume":"38","author":"Wang","year":"2015","journal-title":"Surv. Mapp. Spat. Geogr. Inf."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Qiu, C., Wei, J., and Dong, Q. (2018, January 18\u201320). Research of Image Fusion Method about ZY-3 Panchromatic Image and Multispectral Image. Proceedings of the 2018 Fifth International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Xi\u2019an, China.","DOI":"10.1109\/EORSA.2018.8598582"},{"key":"ref_12","first-page":"45","article-title":"Problems and improvement measures in high-resolution remote sensing image fusion","volume":"4","author":"Zhen","year":"2005","journal-title":"Remote Sens. Inf."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1268","DOI":"10.1080\/10106049.2016.1206627","article-title":"A Comparative Analysis of Pansharpening Techniques on QuickBird and WorldView-3 Images","volume":"32","author":"Snehmani","year":"2017","journal-title":"Geocarto Int."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"8446","DOI":"10.3390\/rs6098446","article-title":"A Bidimensional Empirical Mode Decomposition Method for Fusion of Multispectral and Panchromatic Remote Sensing Images","volume":"6","author":"Dong","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.inffus.2018.11.014","article-title":"The Fusion of Panchromatic and Multispectral Remote Sensing Images via Tensor-Based Sparse Modeling and Hyper-Laplacian Prior","volume":"52","author":"Deng","year":"2019","journal-title":"Inf. Fusion"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"158908","DOI":"10.1109\/ACCESS.2021.3131268","article-title":"Remote Sensing Image Fusion Based on Nonnegative Dictionary Learning","volume":"9","author":"Wang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_17","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_18","doi-asserted-by":"crossref","first-page":"6169","DOI":"10.1109\/TGRS.2019.2904659","article-title":"Spatial\u2013Spectral Fusion by Combining Deep Learning and Variational Model","volume":"57","author":"Shen","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5402016","DOI":"10.1109\/TGRS.2021.3088313","article-title":"PSCSC-Net: A Deep Coupled Convolutional Sparse Coding Network for Pansharpening","volume":"60","author":"Yin","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","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_21","unstructured":"Padwick, C., Scientist, P., Deskevich, M.P., and Smallwood, S.R. (2010, January 26\u201330). WORLDVIEW-2 PAN-SHARPENING. Proceedings of the ASRPS 2010 Annual Conference, San Diego, CA, USA."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","unstructured":"Lu, H., Qiao, D., Li, Y., Wu, S., and Deng, L. (2021). Fusion of China ZY-1 02D Hyperspectral Data and Multispectral Data: Which Methods Should Be Used?. Remote Sens., 13.","DOI":"10.3390\/rs13122354"},{"key":"ref_24","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_25","first-page":"47","article-title":"Comparative analysis of image fusion algorithms of Ziyuan-3 satellite","volume":"40","author":"Wang","year":"2015","journal-title":"Surv. Mapp. Sci."},{"key":"ref_26","unstructured":"Shao, Y., Zhu, C., Zhang, X., and Shen, Q. (2019). Comparison and evaluation of domestic high-resolution satellite remote sensing image fusion methods. Bull. Surv. Mapp., 5\u201310."},{"key":"ref_27","first-page":"91","article-title":"Comparison and evaluation of \u201cGaofen-2\u201d satellite image fusion methods","volume":"38","author":"Xue","year":"2017","journal-title":"Space Return Remote Sens."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/5\/1410\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:03:07Z","timestamp":1760104987000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/5\/1410"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,22]]},"references-count":27,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["s24051410"],"URL":"https:\/\/doi.org\/10.3390\/s24051410","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2024,2,22]]}}}