{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T17:22:29Z","timestamp":1781025749539,"version":"3.54.1"},"reference-count":46,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T00:00:00Z","timestamp":1681689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61675036"],"award-info":[{"award-number":["61675036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>It is a big challenge to quickly and accurately recognize targets in a complex background. The mutual constraints between a wide field of vision (FOV) and high resolution affect the optical tracking and imaging ability in a wide area. In nature, raptors possess unique imaging structures and optic nerve systems that can accurately recognize prey. This paper proposes an imaging system combined with a deep learning algorithm based on the visual characteristics of raptors, aiming to achieve wide FOV, high spatial resolution, and accurate recognition ability. As for the imaging system, two sub-optical systems with different focal lengths and various-size photoreceptor cells jointly simulate the deep fovea of a raptor\u2019s eye. The one simulating the peripheral region has a wide FOV and high sensitivity for capturing the target quickly by means of short focal length and large-size photoreceptor cells, and the other imitating the central region has high resolution for recognizing the target accurately through the long focal length and small-size photoreceptor cells. Furthermore, the proposed algorithm with an attention and feedback network based on octave convolution (AOCNet) simulates the mechanism of the optic nerve pathway by adding it into the convolutional neural network (CNN), thereby enhancing the ability of feature extraction and target recognition. Experimental results show that the target imaging and recognition system eliminates the limitation between wide FOV and high spatial resolution, and effectively improves the accuracy of target recognition in complex backgrounds.<\/jats:p>","DOI":"10.3390\/rs15082106","type":"journal-article","created":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T02:02:59Z","timestamp":1681696979000},"page":"2106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Target Imaging and Recognition Method Based on Raptor Vision"],"prefix":"10.3390","volume":"15","author":[{"given":"Bitong","family":"Xu","sequence":"first","affiliation":[{"name":"College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5275-1728","authenticated-orcid":false,"given":"Zhengzhou","family":"Li","sequence":"additional","affiliation":[{"name":"College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bei","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxin","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abubakar","family":"Siddique","sequence":"additional","affiliation":[{"name":"College of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1109\/TSMCC.2004.829274","article-title":"A Survey on Visual Surveillance of Object Motion and Behaviors","volume":"34","author":"Hu","year":"2004","journal-title":"IEEE Trans. Syst. Man, Cybern. Part C (Appl. Rev.)"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1109\/34.982903","article-title":"Vision for Mobile Robot Navigation: A Survey","volume":"24","author":"Desouza","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3982","DOI":"10.1073\/pnas.1517953113","article-title":"Artificial Eye for Scotopic Vision with Bioinspired All-Optical Photosensitivity Enhancer","volume":"113","author":"Liu","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2468","DOI":"10.1109\/TIM.2014.2343392","article-title":"Visual Measurement in Simulation Environment for Vision-Based UAV Autonomous Aerial Refueling","volume":"64","author":"Duan","year":"2015","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.1109\/TIE.2011.2161248","article-title":"A Robust Real-Time Embedded Vision System on an Unmanned Rotorcraft for Ground Target Following","volume":"59","author":"Lin","year":"2012","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1109\/TSMC.2013.2280121","article-title":"Neural Background Subtraction for Pan-Tilt-Zoom Cameras","volume":"44","author":"Ferone","year":"2014","journal-title":"IEEE Trans. Syst. Man, Cybern. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1109\/TSMC.2015.2491878","article-title":"Vision-Based Target Detection and Localization via a Team of Cooperative UAV and UGVs","volume":"46","author":"Minaeian","year":"2016","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_8","first-page":"3926","article-title":"Optical Imaging of Hidden Objects behind Clothing","volume":"49 20","author":"Granot","year":"2010","journal-title":"Appl. Opt."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5496","DOI":"10.1364\/AO.424547","article-title":"Automatic Optical Inspection Platform for Real-Time Surface Defects Detection on Plane Optical Components Based on Semantic Segmentation","volume":"60","author":"Karangwa","year":"2021","journal-title":"Appl. Opt."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1016\/j.infrared.2012.07.002","article-title":"Analysis of Space Target Detection Range Based on Space-Borne Fisheye Imaging System in Deep Space Background","volume":"55","author":"Huang","year":"2012","journal-title":"Infrared Phys. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"9267","DOI":"10.1073\/pnas.1219068110","article-title":"Miniature Curved Artificial Compound Eyes","volume":"110","author":"Floreano","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1109\/TRO.2010.2042537","article-title":"Steering by Gazing: An Efficient Biomimetic Control Strategy for Visually Guided Micro Aerial Vehicles","volume":"26","author":"Kerhuel","year":"2010","journal-title":"IEEE Trans. Robot."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"126458","DOI":"10.1016\/j.optcom.2020.126458","article-title":"A Single Ball Lens-Based Hybrid Biomimetic Fish Eye\/Compound Eye Imaging System","volume":"480","author":"Lu","year":"2021","journal-title":"Opt. Commun."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1053\/j.jepm.2007.03.012","article-title":"Avian Vision: A Review of Form and Function with Special Consideration to Birds of Prey","volume":"16","author":"Jones","year":"2007","journal-title":"J. Exot. Pet Med."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Liu, K., Huang, J., and Li, X. (2022). Eagle-Eye-Inspired Attention for Object Detection in Remote Sensing. Remote Sens., 14.","DOI":"10.3390\/rs14071743"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s00435-020-00512-2","article-title":"Foveal Shape, Ultrastructure and Photoreceptor Composition in Yellow-Legged Gull, Larus Michahellis (Naumann, 1840)","volume":"140","author":"Victory","year":"2021","journal-title":"Zoomorphology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1038\/275127a0","article-title":"Telephoto Lens System of Falconiform Eyes","volume":"275","author":"Snyder","year":"1978","journal-title":"Nature"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/MAES.2013.6693667","article-title":"Biological Eagle-Eye - Based Visual Imaging Guidance Simulation Platform for Unmanned Flying Vehicles","volume":"28","author":"Duan","year":"2013","journal-title":"IEEE Aerosp. Electron. Syst. Mag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3125","DOI":"10.1109\/TAES.2018.2845178","article-title":"Biological Eagle-Eye-Based Visual Platform for Target Detection","volume":"54","author":"Deng","year":"2018","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1007\/s11277-020-07721-4","article-title":"Eagle Eye CBVR Based on Unique Key Frame Extraction and Deep Belief Neural Network","volume":"116","author":"Prathiba","year":"2021","journal-title":"Wirel. Pers. Commun."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1023\/B:VISI.0000029666.37597.d3","article-title":"Active Appearance Models Revisited","volume":"2","author":"Matthews","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"8331","DOI":"10.1080\/01431161.2010.540587","article-title":"Semi-Automatic Road Tracking by Template Matching and Distance Transformation in Urban Areas","volume":"32","author":"Zhang","year":"2011","journal-title":"Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.isprsjprs.2013.12.011","article-title":"Efficient, Simultaneous Detection of Multi-Class Geospatial Targets Based on Visual Saliency Modeling and Discriminative Learning of Sparse Coding","volume":"89","author":"Han","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"6508","DOI":"10.1109\/TGRS.2013.2296782","article-title":"VHR Object Detection Based on Structural Feature Extraction and Query Expansion","volume":"52","author":"Bai","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4511","DOI":"10.1109\/TGRS.2013.2282355","article-title":"Ship Detection in High-Resolution Optical Imagery Based on Anomaly Detector and Local Shape Feature","volume":"52","author":"Shi","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1109\/LGRS.2018.2889247","article-title":"A Sample Update-Based Convolutional Neural Network Framework for Object Detection in Large-Area Remote Sensing Images","volume":"16","author":"Hu","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4483","DOI":"10.1109\/TGRS.2015.2400462","article-title":"Robust Rooftop Extraction From Visible Band Images Using Higher Order CRF","volume":"53","author":"Li","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"7405","DOI":"10.1109\/TGRS.2016.2601622","article-title":"Learning Rotation-Invariant Convolutional Neural Networks for Object Detection in VHR Optical Remote Sensing Images","volume":"54","author":"Cheng","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Han, X., Zhong, Y., and Zhang, L. (2017). An Efficient and Robust Integrated Geospatial Object Detection Framework for High Spatial Resolution Remote Sensing Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9070666"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7090","DOI":"10.1109\/TIP.2021.3101398","article-title":"DeepFoveaNet: Deep Fovea Eagle-Eye Bioinspired Model to Detect Moving Objects","volume":"30","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wang, S., Fu, Q., Hu, Y., Zhang, C., and He, W. (2021, January 22\u201324). A Miniature Biological Eagle-Eye Vision System for Small Target Detection. Proceedings of the 2021 China Automation Congress (CAC), Beijing, China.","DOI":"10.1109\/CAC53003.2021.9727530"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1002\/cne.901670407","article-title":"Organization of the Tectofugal Visual Pathway in the Pigeon: A Retrograde Transport Study","volume":"167","author":"Benowitz","year":"1976","journal-title":"J. Comp. Neurol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3368","DOI":"10.1109\/TAES.2021.3075524","article-title":"Unmanned Aerial Vehicle Recognition of Maritime Small-Target Based on Biological Eagle-Eye Vision Adaptation Mechanism","volume":"57","author":"Duan","year":"2021","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1477","DOI":"10.1016\/0042-6989(85)90226-3","article-title":"Spatial Visual Acuity of the Eagle Aquila Audax: A Behavioural, Optical and Anatomical Investigation","volume":"25","author":"Reymond","year":"1985","journal-title":"Vis. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2053","DOI":"10.1016\/S0042-6989(03)00304-3","article-title":"The Visual Acuity and Refractive State of the American Kestrel (Falco Sparverius)","volume":"43","author":"Gaffney","year":"2003","journal-title":"Vis. Res."},{"key":"ref_36","first-page":"379","article-title":"Relative Contributions of the Two Visual Pathways to Avian Behaviour","volume":"52","author":"Deng","year":"2006","journal-title":"Acta Zoo."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Chen, Y., Fan, H., Xu, B., Yan, Z., Kalantidis, Y., Rohrbach, M., Shuicheng, Y., and Feng, J. (November, January 27). Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks With Octave Convolution. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Republic of Korea.","DOI":"10.1109\/ICCV.2019.00353"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., and Kweon, I.S. (2018, January 8\u201314). CBAM: Convolutional Block Attention Module. Proceedings of the European Conference on Computer Vision, Munich, Germany.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Su, H., Wei, S., Yan, M., Wang, C., Shi, J., and Zhang, X. (August, January 28). Object Detection and Instance Segmentation in Remote Sensing Imagery Based on Precise Mask R-CNN. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898573"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Su, H., Wei, S., Liu, S., Liang, J., Wang, C., Shi, J., and Zhang, X. (2020). HQ-ISNet: High-Quality Instance Segmentation for Remote Sensing Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12060989"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"23729","DOI":"10.1007\/s11042-020-08976-6","article-title":"A Review of Object Detection Based on Deep Learning","volume":"79","author":"Xiao","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Zhang, H., Chang, H., Ma, B., Wang, N., and Chen, X. (2020, January 23\u201328). Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training. Proceedings of the ECCV, Glasgow, UK.","DOI":"10.1007\/978-3-030-58555-6_16"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., and Berg, A.C. (2016, January 11\u201314). SSD: Single shot multibox detector. Proceedings of the 14th ECCV, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"ref_45","unstructured":"Redmon, J., and Farhadi, A. (2018, January 18\u201322). YOLOv3: An Incremental Improvement. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., and Belongie, S. (2017, January 21\u201326). Feature Pyramid Networks for Object Detection. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.106"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2106\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:17:02Z","timestamp":1760123822000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2106"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,17]]},"references-count":46,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15082106"],"URL":"https:\/\/doi.org\/10.3390\/rs15082106","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,17]]}}}