{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:16:03Z","timestamp":1760148963584,"version":"build-2065373602"},"reference-count":59,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,6,25]],"date-time":"2023-06-25T00:00:00Z","timestamp":1687651200000},"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":["62261004","62001129"],"award-info":[{"award-number":["62261004","62001129"]}],"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 difficult for traditional algorithms to remove cloud edge contours in multi-cloud scenarios. In order to improve the detection ability of dim and small targets in complex edge contour scenes, this paper proposes a new dim and small target detection algorithm based on local multi-directional gradient information energy perception. Herein, based on the information difference between the target area and the background area in the four direction neighborhood blocks, an energy enhancement model for multi-directional gray aggregation (EMDGA) is constructed to preliminarily enhance the target signal. Subsequently, a local multi-directional gradient reciprocal background suppression model (LMDGR) was constructed to model the background of the image. Furthermore, this paper proposes a multi-directional gradient scale segmentation model (MDGSS) to obtain candidate target points and then combines the proposed multi-frame energy-sensing (MFESD) detection algorithm to extract the true targets from sequence images. Finally, in order to better illustrate the effect of the algorithm proposed in this paper in detecting small targets in a cloudy background, four sequence images are selected for detection. The experimental results show that the proposed algorithm can effectively suppress the edge contour of complex clouds compared with the traditional algorithm. When the false alarm rate Pf is 0.005%, the detection rate Pd is greater than 95%.<\/jats:p>","DOI":"10.3390\/rs15133267","type":"journal-article","created":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T03:14:56Z","timestamp":1687749296000},"page":"3267","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Dim and Small Target Detection Based on Energy Sensing of Local Multi-Directional Gradient Information"],"prefix":"10.3390","volume":"15","author":[{"given":"Xiangsuo","family":"Fan","sequence":"first","affiliation":[{"name":"School of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China"},{"name":"Guangxi Collaborative Innovation Centre for Earthmoving Machinery, Guangxi University of Science and Technology, Liuzhou 545006, China"}]},{"given":"Juliu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China"}]},{"given":"Lei","family":"Min","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"}]},{"given":"Linping","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}]},{"given":"Ling","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China"}]},{"given":"Zhiyong","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107729","DOI":"10.1016\/j.patcog.2020.107729","article-title":"Infrared small target detection via adaptive M-estimator ring top-hat transformation","volume":"112","author":"Deng","year":"2021","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.patcog.2016.04.001","article-title":"Small dim object tracking using frequency and spatial domain information","volume":"58","author":"Ahmadi","year":"2016","journal-title":"Pattern Recognit."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"910002","DOI":"10.3788\/gzxb20154409.0910002","article-title":"Infrared Dim and Small Target Detection Algorithm Based on Multi-scale Anisotropic Diffusion Equation","volume":"44","author":"Zhou","year":"2015","journal-title":"Acta Photonica Sin."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.infrared.2015.03.007","article-title":"Small infrared target detection utilizing Local Region Similarity Difference map","volume":"71","author":"Qi","year":"2015","journal-title":"Infrared Phys. 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