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ZZU-CISS-2024003"]}]},{"name":"the Open Found of the Engineering Research Center of Intelligent Swarm Systems, Ministry of Education","award":["231100220300"],"award-info":[{"award-number":["231100220300"]}]},{"name":"the Open Found of the Engineering Research Center of Intelligent Swarm Systems, Ministry of Education","award":["231100220400"],"award-info":[{"award-number":["231100220400"]}]},{"name":"the Open Found of the Engineering Research Center of Intelligent Swarm Systems, Ministry of Education","award":["no. 21A510003"],"award-info":[{"award-number":["no. 21A510003"]}]},{"name":"the Open Found of the Engineering Research Center of Intelligent Swarm Systems, Ministry of Education","award":["no. 222102210053"],"award-info":[{"award-number":["no. 222102210053"]}]},{"name":"the Open Found of the Engineering Research Center of Intelligent Swarm Systems, Ministry of Education","award":["no. ZZU-CISS-2024003"],"award-info":[{"award-number":["no. ZZU-CISS-2024003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Semantic communication is an emerging approach that enhances transmission efficiency by conveying the semantic content of information more effectively. It has garnered significant attention in recent years. However, existing semantic communication systems for image transmission typically adopt direct transmission of features or uniformly compress features before transmission. They have not yet considered the differential impact of features on image recovery at the receiver end and the issue of bandwidth limitations during actual transmission. This paper shows that non-uniform processing of features leads to better image recovery under bandwidth constraints compared to uniform processing. Based on this, we propose a semantic communication system for image transmission, which introduces non-uniform quantization techniques. In the feature transmission stage, the system performs varying levels of quantization based on the differences in feature performance at the receiver, thereby reducing the bandwidth requirement. Inspired by quantitative quantization techniques, we design a non-uniform quantization algorithm capable of dynamic bit allocation. This algorithm, under bandwidth constraints, dynamically adjusts the quantization precision of features based on their contribution to the completion of tasks at the receiver end, ensuring the quality and accuracy of the transmitted data even under limited bandwidth conditions. Experimental results show that the proposed system reduces bandwidth usage while ensuring image reconstruction quality.<\/jats:p>","DOI":"10.3390\/e27040369","type":"journal-article","created":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T08:48:00Z","timestamp":1743410880000},"page":"369","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Feature-Driven Semantic Communication for Efficient Image Transmission"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7642-7607","authenticated-orcid":false,"given":"Ji","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, China"},{"name":"Intelligent System Science and Technology Innovation Center, Longmen Laboratory, Luoyang 471000, China"},{"name":"Engineering Research Center of Intelligent Swarm Systems, Ministry of Education, Zhengzhou University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, China"},{"name":"Intelligent System Science and Technology Innovation Center, Longmen Laboratory, Luoyang 471000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baofeng","family":"Ji","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, China"},{"name":"Intelligent System Science and Technology Innovation Center, Longmen Laboratory, Luoyang 471000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anmin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, China"},{"name":"Intelligent System Science and Technology Innovation Center, Longmen Laboratory, Luoyang 471000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aoxue","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, China"},{"name":"Intelligent System Science and Technology Innovation Center, Longmen Laboratory, Luoyang 471000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hengzhou","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer, Henan University of Engineering, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1360\/SSI-2020-0086","article-title":"Shannon theory and future 6G\u2019s technique potentials","volume":"50","author":"You","year":"2020","journal-title":"Sci. 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