{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T15:22:57Z","timestamp":1777389777637,"version":"3.51.4"},"reference-count":27,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T00:00:00Z","timestamp":1725321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities","award":["226-2023-00154"],"award-info":[{"award-number":["226-2023-00154"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2018YFB0505002"],"award-info":[{"award-number":["2018YFB0505002"]}]},{"name":"National Key Research and Development Program of China","award":["226-2023-00154"],"award-info":[{"award-number":["226-2023-00154"]}]},{"name":"National Key Research and Development Program of China","award":["2018YFB0505002"],"award-info":[{"award-number":["2018YFB0505002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing allows us to conduct large-scale scientific studies that require extensive mapping and the amalgamation of numerous images. However, owing to variations in radiation, atmospheric conditions, sensor perspectives, and land cover, significant color discrepancies often arise between different images, necessitating color consistency adjustments for effective image mosaicking and applications. Existing methods for color consistency adjustment in remote sensing images struggle with complex one-to-many nonlinear color-mapping relationships, often resulting in texture distortions. To address these challenges, this study proposes a convolutional neural network-based color consistency method for remote sensing cartography that considers both global and local color mapping and texture mapping constrained by the source domain. This method effectively handles complex color-mapping relationships while minimizing texture distortions in the target image. Comparative experiments on remote sensing images from different times, sensors, and resolutions demonstrated that our method achieved superior color consistency, preserved fine texture details, and provided visually appealing outcomes, assisting in generating large-area data products.<\/jats:p>","DOI":"10.3390\/rs16173269","type":"journal-article","created":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T08:38:47Z","timestamp":1725352727000},"page":"3269","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Texture-Considerate Convolutional Neural Network Approach for Color Consistency in Remote Sensing Imagery"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2424-1562","authenticated-orcid":false,"given":"Xiaoyuan","family":"Qian","sequence":"first","affiliation":[{"name":"Institute for Geography and Spatial Information, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3540-0309","authenticated-orcid":false,"given":"Cheng","family":"Su","sequence":"additional","affiliation":[{"name":"Institute for Geography and Spatial Information, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1355-2854","authenticated-orcid":false,"given":"Shirou","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute for Geography and Spatial Information, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2149-9109","authenticated-orcid":false,"given":"Zeyu","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute for Geography and Spatial Information, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaocan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute for Geography and Spatial Information, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,3]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Algorithm\/Hardware Codesign for Real-Time On-Satellite CNN-Based Ship Detection in SAR Imagery","volume":"60","author":"Yang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.eng.2019.12.009","article-title":"On the Future: A Keynote Address","volume":"6","author":"Rees","year":"2020","journal-title":"Engineering"},{"key":"ref_3","first-page":"42","article-title":"Global Change Study and Remote Sensing Technology","volume":"2","author":"Gao","year":"2000","journal-title":"Geo-Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.isprsjprs.2015.02.009","article-title":"UAV Photogrammetry for Topographic Monitoring of Coastal Areas","volume":"104","author":"Henriques","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2244672","article-title":"Hyperspectral Remote Sensing Data Analysis and Future Challenges","volume":"1","author":"Plaza","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rse.2011.08.024","article-title":"A Review of Large Area Monitoring of Land Cover Change using Landsat Data","volume":"122","author":"Hansen","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1186\/s13640-018-0323-5","article-title":"Remote Sensing Image Mosaic Technology Based on SURF Algorithm in Agriculture","volume":"2018","author":"Zhang","year":"2018","journal-title":"EURASIP J. Image Video Process."},{"key":"ref_8","first-page":"51","article-title":"Review of Dodging Algorithm of Remote Sensing Image","volume":"6","author":"Wang","year":"2017","journal-title":"Jiangsu Sci. Technol. Inf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2022.05.009","article-title":"A Unified Probabilistic Framework of Robust and Efficient Color Consistency Correction for Multiple Images","volume":"190","author":"Li","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.rse.2006.03.008","article-title":"Radiometric Correction of Multi-temporal Landsat Data for Characterization of Early Successional Forest Patterns in Western Oregon","volume":"103","author":"Schroeder","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Li, Z., Zhu, H., and Zhou, C. (2020). A Color Consistency Processing Method for HY-1C Images of Antarctica. Remote Sens., 12.","DOI":"10.3390\/rs12071143"},{"key":"ref_12","first-page":"24","article-title":"The Image Matching Based on Wallis Filtering","volume":"1","author":"Zhang","year":"1999","journal-title":"J. Wuhan Tech. Univ. Surv. Mapp."},{"key":"ref_13","first-page":"753","article-title":"Auto-dodging Processing and Its Application for Optical RS Images","volume":"9","author":"Li","year":"2006","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Yeganeh, H., Ziaei, A., and Rezaie, A. (2008, January 13\u201315). A Novel Approach for Contrast Enhancement Based on Histogram Equalization. Proceedings of the International Conference on Computer and Communication Engineering, Kuala Lumpur, Malaysia.","DOI":"10.1109\/ICCCE.2008.4580607"},{"key":"ref_15","unstructured":"Jensen, J.R. (1996). Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice Hall. [2nd ed.]."},{"key":"ref_16","unstructured":"Gonzalez, R.C., and Woods, R.E. (2008). Digital Image Processing, Person Prentice Hall. [3rd ed.]."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1364\/JOSAA.3.000735","article-title":"Color Equalization Method and Its Application to Color Image Processing","volume":"3","author":"Bockstein","year":"1986","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1117\/1.1353200","article-title":"Adaptive-neighborhood Histogram Equalization of Color Images","volume":"10","author":"Buzuloiu","year":"2001","journal-title":"J. Electron. Imaging"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Acharya, T., and Ray, A.K. (2005). Image Processing: Principles and Applications, Wiley-Interscience.","DOI":"10.1002\/0471745790"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.isprsjprs.2019.09.004","article-title":"A Closed-form Solution for Multi-view Color Correction with Gradient Preservation","volume":"157","author":"Xia","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2972","DOI":"10.1109\/TGRS.2017.2657582","article-title":"A Mixed Radiometric Normalization Method for Mosaicking of High-Resolution Satellite Imagery","volume":"55","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"6141","DOI":"10.1109\/TGRS.2013.2295263","article-title":"Automatic Radiometric Normalization for Multitemporal Remote Sensing Imagery with Iterative Slow Feature Analysis","volume":"52","author":"Zhang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Xia, M., Yao, J., and Xie, R. (2017, January 22\u201329). Color Consistency Correction Based on Remapping Optimization for Image Stitching. Proceedings of the IEEE International Conference on Computer Vision Workshops, Venice, Italy.","DOI":"10.1109\/ICCVW.2017.351"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1167\/16.12.326","article-title":"A Neural Algorithm of Artistic Style","volume":"16","author":"Gatys","year":"2016","journal-title":"J. Vis."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"7178","DOI":"10.1109\/TGRS.2020.2980417","article-title":"ColorMapGAN: Unsupervised Domain Adaptation for Semantic Segmentation Using Color Mapping Generative Adversarial Networks","volume":"58","author":"Tasar","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Benjdira, B., Bazi, Y., and Koubaa, A. (2019). Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images. Remote Sens., 11.","DOI":"10.3390\/rs11111369"},{"key":"ref_27","first-page":"1473","article-title":"Multi-temporal Remote Sensing Imagery Semantic Segmentation Color Consistency Adversarial Network","volume":"49","author":"Li","year":"2020","journal-title":"Acta Geod. Cartogr. Sin."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3269\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:47:55Z","timestamp":1760111275000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3269"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,3]]},"references-count":27,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["rs16173269"],"URL":"https:\/\/doi.org\/10.3390\/rs16173269","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,3]]}}}