{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T10:29:47Z","timestamp":1778754587770,"version":"3.51.4"},"reference-count":21,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,3,19]],"date-time":"2023-03-19T00:00:00Z","timestamp":1679184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Satellite image compression technology plays an important role in the development of space science. As optical sensors on satellites become more sophisticated, high-resolution and high-fidelity satellite images will occupy more storage. This raises the required transmission bandwidth and transmission rate in the satellite\u2013ground data transmission system. In order to reduce the pressure from image transmission on the data transmission system, a spaceborne target detection system based on Yolov5 and a satellite image compression transmission system is proposed in this paper. It can reduce the pressure on the data transmission system by detecting the object of interest and deciding whether to transmit. An improved Yolov5 network is proposed to detect the small target on the high-resolution satellite image. Simulation results show that the improved Yolov5 network proposed in this paper can detect specific targets in real satellite images, including aircraft, ships, etc. At the same time, image compression has little effect on target detection, so detection complexity can be effectively reduced and detection speed can be improved by detecting the compressed images.<\/jats:p>","DOI":"10.3390\/fi15030114","type":"journal-article","created":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T02:38:27Z","timestamp":1679279907000},"page":"114","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Research on Spaceborne Target Detection Based on Yolov5 and Image Compression"],"prefix":"10.3390","volume":"15","author":[{"given":"Qi","family":"Shi","sequence":"first","affiliation":[{"name":"Innovation Academy for Microsatellites of Chinese Academy of Sciences, Shanghai 201304, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daheng","family":"Wang","sequence":"additional","affiliation":[{"name":"China Satellite Network Group Co., Ltd., Beijing 100000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Chen","sequence":"additional","affiliation":[{"name":"Innovation Academy for Microsatellites of Chinese Academy of Sciences, Shanghai 201304, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinpei","family":"Yu","sequence":"additional","affiliation":[{"name":"Innovation Academy for Microsatellites of Chinese Academy of Sciences, Shanghai 201304, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100039, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiting","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1655-9197","authenticated-orcid":false,"given":"Jun","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangzu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,19]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Effects of Lossy Compression on Remote Sensing Image Classification Based on Convolutional Sparse Coding","volume":"19","author":"Wei","year":"2022","journal-title":"IEEE Geosci. 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