{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T22:27:14Z","timestamp":1770071234012,"version":"3.49.0"},"reference-count":46,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T00:00:00Z","timestamp":1726272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>This paper presents a novel hybrid approach to feature detection designed specifically for enhancing Feature-Based Image Registration (FBIR). Through an extensive evaluation involving state-of-the-art feature detectors such as BRISK, FAST, ORB, Harris, MinEigen, and MSER, the proposed hybrid detector demonstrates superior performance in terms of keypoint detection accuracy and computational efficiency. Three image acquisition methods (i.e., rotation, scene-to-model, and scaling transformations) are considered in the comparison. Applied across a diverse set of remote-sensing images, the proposed hybrid approach has shown marked improvements in match points and match rates, proving its effectiveness in handling varied and complex imaging conditions typical in satellite and aerial imagery. The experimental results have consistently indicated that the hybrid detector outperforms conventional methods, establishing it as a valuable tool for advanced image registration tasks.<\/jats:p>","DOI":"10.3390\/jimaging10090228","type":"journal-article","created":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T07:36:00Z","timestamp":1726472160000},"page":"228","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Hybrid Approach for Image Acquisition Methods Based on Feature-Based Image Registration"],"prefix":"10.3390","volume":"10","author":[{"given":"Anchal","family":"Kumawat","sequence":"first","affiliation":[{"name":"Department of Computer Science Engineering and Application, Sambalpur University Institute of Information Technology (SUIIT), Burla, Sambalpur 768018, India"}]},{"given":"Sucheta","family":"Panda","sequence":"additional","affiliation":[{"name":"School of Computer Sciences, Veer Surendra Sai University of Technology (VSSUT), Burla, Sambalpur 768018, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9895-7606","authenticated-orcid":false,"given":"Vassilis C.","family":"Gerogiannis","sequence":"additional","affiliation":[{"name":"Department of Digital Systems, University of Thessaly, 41500 Larissa, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9964-4134","authenticated-orcid":false,"given":"Andreas","family":"Kanavos","sequence":"additional","affiliation":[{"name":"Department of Informatics, Ionian University, 49100 Corfu, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6506-9207","authenticated-orcid":false,"given":"Biswaranjan","family":"Acharya","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering-AI, Marwadi University, Rajkot 360003, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8790-9409","authenticated-orcid":false,"given":"Stella","family":"Manika","sequence":"additional","affiliation":[{"name":"Department of Planning and Regional Development, University of Thessaly, 38334 Volos, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yuan, W., Poosa, S.R.P., and Dirks, R.F. (2024). Comparative Analysis of Color Space and Channel, Detector, and Descriptor for Feature-Based Image Registration. J. Imaging, 10.","DOI":"10.3390\/jimaging10050105"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2351","DOI":"10.1109\/36.789634","article-title":"A Feature-based Image Registration Algorithm using Improved Chain-Code Representation Combined with Invariant Moments","volume":"37","author":"Dai","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1186\/s10033-018-0275-9","article-title":"A Review of Point Feature Based Medical Image Registration","volume":"31","author":"Guan","year":"2018","journal-title":"Chin. J. Mech. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/19479832.2019.1707720","article-title":"An Overview of Deep Learning Methods for Image Registration with Focus on Feature-based Approaches","volume":"11","author":"Kuppala","year":"2020","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.procs.2018.05.176","article-title":"Feature Detection and Description in Remote Sensing Images Using a Hybrid Feature Detector","volume":"132","author":"Kumawat","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kumawat, A., and Panda, S. (2020). Feature Extraction and Matching of River Dam Images in Odisha Using a Novel Feature Detector. Proceedings of the Computational Intelligence in Pattern Recognition (CIPR), Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-981-13-9042-5_61"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Pratt, W.K. (2007). Digital Image Processing: PIKS Scientific Inside, Wiley Online Library.","DOI":"10.1002\/0470097434"},{"key":"ref_8","unstructured":"Sridhar (2011). Digital Image Processing, Oxford University Press, Inc."},{"key":"ref_9","unstructured":"Zitova, B., Flusser, J., and Sroubek, F. (2005, January 11\u201314). Image Registration: A Survey and Recent Advances. Proceedings of the International Conference on Image Processing, Genoa, Italy."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18100\/ijamec.60004","article-title":"A Comparative Evaluation of Well-Known Feature Detectors and Descriptors","volume":"3","year":"2014","journal-title":"Int. J. Appl. Math. Electron. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1109\/TPAMI.2005.188","article-title":"A Performance Evaluation of Local Descriptors","volume":"27","author":"Mikolajczyk","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"ref_12","unstructured":"Mamadou, D., Gouton, P., and Adou, K.J. (December, January 28). A Comparative Study of Descriptors and Detectors in Multispectral Face Recognition. Proceedings of the 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Naples, Italy."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Rana, S., Gerbino, S., Crimaldi, M., Cirillo, V., Carillo, P., Sarghini, F., and Maggio, A. (2024). Comprehensive Evaluation of Multispectral Image Registration Strategies in Heterogenous Agriculture Environment. J. Imaging, 10.","DOI":"10.2139\/ssrn.4687970"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Abraham, E., Mishra, S., Tripathi, N., and Sukumaran, G. (2013, January 21\u201322). HOG Descriptor Based Registration (A New Image Registration Technique). Proceedings of the 15th International Conference on Advanced Computing Technologies (ICACT), Rajampet, India.","DOI":"10.1109\/ICACT.2013.6710513"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2390","DOI":"10.1016\/j.procs.2020.04.259","article-title":"Remote Sensing Image Registration Methodology: Review and Discussion","volume":"171","author":"Tondewad","year":"2020","journal-title":"Procedia Comput. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhang, X., Leng, C., Hong, Y., Pei, Z., Cheng, I., and Basu, A. (2021). Multimodal Remote Sensing Image Registration Methods and Advancements: A Survey. Remote Sens., 13.","DOI":"10.3390\/rs13245128"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"107377","DOI":"10.1016\/j.patcog.2020.107377","article-title":"Non-Rigid Infrared and Visible Image Registration by Enhanced Affine Transformation","volume":"106","author":"Min","year":"2020","journal-title":"Pattern Recognit."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kahaki, S.M.M., Nordin, M.J., Ashtari, A.H., and Zahra, S.J. (2016). Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0149710"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Salahat, E., and Qasaimeh, M. (2017, January 22\u201325). Recent Advances in Features Extraction and Description Algorithms: A Comprehensive Survey. Proceedings of the International Conference on Industrial Technology (ICIT), Toronto, ON, Canada.","DOI":"10.1109\/ICIT.2017.7915508"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"103691","DOI":"10.1016\/j.infrared.2021.103691","article-title":"A Robust Deformed Image Matching Method for Multi-Source Image Matching","volume":"115","author":"Xu","year":"2021","journal-title":"Infrared Phys. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s11263-020-01359-2","article-title":"Image Matching from Handcrafted to Deep Features: A Survey","volume":"129","author":"Ma","year":"2021","journal-title":"Int. J. Comput. Vis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2194","DOI":"10.1109\/JSTARS.2021.3052472","article-title":"Efficient Multisource Remote Sensing Image Matching Using Dominant Orientation of Gradient","volume":"14","author":"Liang","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Liu, X., Xue, J., Xu, X., Lu, Z., Liu, R., Zhao, B., Li, Y., and Miao, Q. (2022). Robust Multimodal Remote Sensing Image Registration Based on Local Statistical Frequency Information. Remote Sens., 14.","DOI":"10.3390\/rs14041051"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hazra, J., Chowdhury, A.R., Dasgupta, K., and Dutta, P. (2022). A Hybrid Structural Feature Extraction-Based Intelligent Predictive Approach for Image Registration. Innovations in Systems and Software Engineering, Springer.","DOI":"10.1007\/s11334-022-00436-8"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Liu, Z., Xu, G., Xiao, J., Yang, J., Wang, Z., and Cheng, S. (2023). A Real-Time Registration Algorithm of UAV Aerial Images Based on Feature Matching. J. Imaging, 9.","DOI":"10.3390\/jimaging9030067"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"8871","DOI":"10.1007\/s11042-022-11901-8","article-title":"A Hybrid Feature Extraction Technique for Content Based Medical Image Retrieval Using Segmentation and Clustering Techniques","volume":"81","author":"Madhu","year":"2022","journal-title":"Multimed. Tools Appl."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zhang, P., Luo, X., Ma, Y., Wang, C., Wang, W., and Qian, X. (2022). Coarse-to-Fine Image Registration for Multi-Temporal High Resolution Remote Sensing Based on a Low-Rank Constraint. Remote Sens., 14.","DOI":"10.3390\/rs14030573"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1007\/s13319-018-0203-x","article-title":"Feature Matching Improvement Through Merging Features for Remote Sensing Imagery","volume":"9","author":"Karim","year":"2018","journal-title":"3D Res."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, D., Wei, H., Huang, X., and Ni, H. (2023, January 6\u20138). Research on High Precision Image Registration Method Based on Line Segment Feature and ICP Algorithm. Proceedings of the International Conference on Optics and Machine Vision (ICOMV), Changsha, China.","DOI":"10.1117\/12.2678654"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"16223","DOI":"10.1007\/s00521-023-08649-z","article-title":"Normal Vibration Distribution Search-Based Differential Evolution Algorithm for Multimodal Biomedical Image Registration","volume":"35","author":"Gui","year":"2023","journal-title":"Neural Comput. Appl."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, W., and Zhao, Y. (2023). SAR and Optical Image Registration Based on Uniform Feature Points Extraction and Consistency Gradient Calculation. Appl. Sci., 13.","DOI":"10.3390\/app13031238"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1109\/TMM.2021.3120873","article-title":"EAPT: Efficient Attention Pyramid Transformer for Image Processing","volume":"25","author":"Lin","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","article-title":"PhotoHelper: Portrait Photographing Guidance Via Deep Feature Retrieval and Fusion","volume":"25","author":"Jiang","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"6662","DOI":"10.1109\/TCYB.2021.3079311","article-title":"Improving Video Temporal Consistency via Broad Learning System","volume":"52","author":"Sheng","year":"2022","journal-title":"IEEE Trans. Cybern."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1109\/TII.2021.3085669","article-title":"Automatic Detection and Classification System of Domestic Waste via Multimodel Cascaded Convolutional Neural Network","volume":"18","author":"Li","year":"2022","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1007\/s00371-021-02199-y","article-title":"GPSD: Generative Parking Spot Detection Using Multi-Clue Recovery Model","volume":"37","author":"Chen","year":"2021","journal-title":"Vis. Comput."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4499","DOI":"10.1109\/TNNLS.2021.3116209","article-title":"BaGFN: Broad Attentive Graph Fusion Network for High-Order Feature Interactions","volume":"34","author":"Xie","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_38","unstructured":"Donoser, M., and Bischof, H. (2006, January 17\u201322). Efficient Maximally Stable Extremal Region (MSER) Tracking. Proceedings of the Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), New York, NY, USA."},{"key":"ref_39","first-page":"430","article-title":"Machine Learning for High-Speed Corner Detection","volume":"Volume 3951","author":"Rosten","year":"2006","journal-title":"Proceedings of the 9th European Conference on Computer Vision (ECCV), Graz, Austria, 7\u201313 May 2006"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Leutenegger, S., Chli, M., and Siegwart, R. (2011, January 6\u201313). BRISK: Binary Robust Invariant Scalable Keypoints. Proceedings of the IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126542"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1109\/TPAMI.2008.275","article-title":"Faster and Better: A Machine Learning Approach to Corner Detection","volume":"32","author":"Rosten","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1166\/jctn.2020.8623","article-title":"A Comparative Study of Feature Detection Techniques for Navigation of Visually Impaired Person in an Indoor Environment","volume":"17","author":"Jeyapal","year":"2020","journal-title":"J. Comput. Theor. Nanosci."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Tareen, S.A.K., and Saleem, Z. (2018, January 3\u20134). A Comparative Analysis of SIFT, SURF, KAZE, AKAZE, ORB, and BRISK. Proceedings of the International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Sukkur, Pakistan.","DOI":"10.1109\/ICOMET.2018.8346440"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"305","DOI":"10.5201\/ipol.2018.229","article-title":"An Analysis and Implementation of the Harris Corner Detector","volume":"8","author":"Salgado","year":"2018","journal-title":"Image Process. Line"},{"key":"ref_45","unstructured":"(2024, August 29). Hybrid Approach for FBIR. Available online: https:\/\/github.com\/Anchal2016\/Hybrid-approach-for-FBIR."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3965","DOI":"10.1109\/TGRS.2017.2685945","article-title":"AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification","volume":"55","author":"Xia","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/10\/9\/228\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:56:27Z","timestamp":1760111787000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/10\/9\/228"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,14]]},"references-count":46,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["jimaging10090228"],"URL":"https:\/\/doi.org\/10.3390\/jimaging10090228","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,14]]}}}