{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T16:34:29Z","timestamp":1771518869333,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T00:00:00Z","timestamp":1725494400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chinese Natural Science Foundation Project","award":["41930111"],"award-info":[{"award-number":["41930111"]}]},{"name":"Chinese Natural Science Foundation Project","award":["42471365"],"award-info":[{"award-number":["42471365"]}]},{"name":"Chinese Natural Science Foundation Project","award":["42071317"],"award-info":[{"award-number":["42071317"]}]},{"name":"Chinese Natural Science Foundation Project","award":["42271362"],"award-info":[{"award-number":["42271362"]}]},{"name":"Chinese Natural Science Foundation Project","award":["42130111"],"award-info":[{"award-number":["42130111"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Stripe noise is a general phenomenon in original remote sensing images that both degrades image quality and severely limits its quantitative application. While the classical statistical method is effective in correcting common stripes caused by inaccurately calibrating relative gains and offsets between detectors, it falls short in correcting other nonlinear stripe noises originating from subtle nonlinear changes or random contamination within the same detector. Therefore, this paper proposes a novel trend repair method based on two normal columns directly adjacent to a defective column to rectify the trend by considering the geospatial structure of contaminated pixels, eliminating residual stripe noise evident in level 0 (L0) remote sensing images after histogram matching. GF5-02 VIMI (Gaofen5-02, visual and infrared multispectral imager) images and simulated Landsat 8 thermal infrared sensor (TIRS) images deliberately infused with stripe noise are selected to test the new method and two other existing methods, the piece-wise method and the iterated weighted least squares (WLS) method. The effectiveness of these three methods is reflected by streaking metrics (Streaking), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and improvement factor (IF) on the uniformity, structure, and information content of the corrected GF5-02 VIMI images and by the accuracy of the corrected simulated Landsat 8 TIRS images. The experimental results indicate that the trend repair method proposed in this paper removes nonlinear stripe noise effectively, making the results of IF &gt; 20. The remaining indicators also show satisfactory results; in particular, the mean accuracy derived from the simulated image remains below a digital number (DN) of 15, which is far superior to the other two methods.<\/jats:p>","DOI":"10.3390\/rs16173299","type":"journal-article","created":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T05:30:02Z","timestamp":1725514202000},"page":"3299","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Stripe Noise Elimination with a Novel Trend Repair Method for Push-Broom Thermal Images"],"prefix":"10.3390","volume":"16","author":[{"given":"Zelin","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3834-2682","authenticated-orcid":false,"given":"Hua","family":"Li","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Yongming","family":"Du","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Yao","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Guoxiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Program of Computer Science, University of Toronto, Toronto, ON M4Y 0C8, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2433-9901","authenticated-orcid":false,"given":"Zunjian","family":"Bian","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Biao","family":"Cao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Innovation Research Center of Satellite Application, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Qing","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"National Engineering Research Center for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3713-9511","authenticated-orcid":false,"given":"Qinhuo","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"National Engineering Research Center for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Liu, J.G. 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