Ran An;Weibo Huo;Yujie Zhang;Jifang Pei;Yin Zhang;Yulin Huang
{"title":"A DCT-Based Local Contrast Enhancement Algorithm in SAR Image Target Detection","authors":"Ran An;Weibo Huo;Yujie Zhang;Jifang Pei;Yin Zhang;Yulin Huang","doi":"10.1109/JSTARS.2025.3602128","DOIUrl":null,"url":null,"abstract":"Synthetic aperture radar (SAR) has become an indispensable remote sensing technology for maritime surveillance. Due to the influence of sea clutter, ship targets may be submerged in background noise, making it difficult for SAR ship target detection. In order to solve this problem, a discrete cosine transform (DCT)-based local contrast enhancement algorithm (DCT-LCE) is proposed in this article. By integrating DCT with sliding window, this algorithm innovatively transforms the SAR image into the DCT domain for processing. A weighted alternating current coefficients calculation method is designed to characterize statistical features within the sliding window, providing a quantitative method for distinguishing between targets and backgrounds. In addition, as optimization and improvement of DCT-LCE, multiscale DCT local contrast enhancement (MDCT-LCE) is proposed to enhance the detailed morphological information of ship targets. Experimental simulations demonstrate that the proposed algorithms can effectively enhance ship targets. Moreover, compared with other sliding window-based algorithms, the proposed algorithms have better detection performance both in accuracy and morphological features under different levels of complexity background.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"18 ","pages":"21688-21699"},"PeriodicalIF":5.3000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11134819","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11134819/","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Synthetic aperture radar (SAR) has become an indispensable remote sensing technology for maritime surveillance. Due to the influence of sea clutter, ship targets may be submerged in background noise, making it difficult for SAR ship target detection. In order to solve this problem, a discrete cosine transform (DCT)-based local contrast enhancement algorithm (DCT-LCE) is proposed in this article. By integrating DCT with sliding window, this algorithm innovatively transforms the SAR image into the DCT domain for processing. A weighted alternating current coefficients calculation method is designed to characterize statistical features within the sliding window, providing a quantitative method for distinguishing between targets and backgrounds. In addition, as optimization and improvement of DCT-LCE, multiscale DCT local contrast enhancement (MDCT-LCE) is proposed to enhance the detailed morphological information of ship targets. Experimental simulations demonstrate that the proposed algorithms can effectively enhance ship targets. Moreover, compared with other sliding window-based algorithms, the proposed algorithms have better detection performance both in accuracy and morphological features under different levels of complexity background.
期刊介绍:
The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.