{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:46:43Z","timestamp":1760240803805,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T00:00:00Z","timestamp":1567987200000},"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":["41371434","61562049"],"award-info":[{"award-number":["41371434","61562049"]}],"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>The Orbita hyperspectral satellite (OHS) is the first hyperspectral satellite with surface coating technology for sensors in the world. It includes 32 bands from visible to near-infrared wavelengths. However, technology such as the fabricating process of complementary metal\u2013oxide\u2013semiconductor (CMOS) sensors makes the image contain a lot of random and unsystematic stripe noise, which is so bad that it seriously affects visual interpretation, object recognition and the application of the OHS data. Although a large number of stripe removal algorithms have been proposed, very few of them take into account the characteristics of OHS sensors and analyze the causes of OHS data noise. In this paper, we propose a destriping algorithm for OHS data. Firstly, we use both the adaptive moment matching method and multi-level unidirectional total variation method to remove stripes. Then a model based on piecewise linear least squares fitting is proposed to restore the vertical details lost in the first step. Moreover, we further utilize the spectral information of the OHS image, and extend our 2-D destriping method to the 3-D case. Results demonstrate that the proposed method provides the optimal destriping result on both qualitative and quantitative assessments. Moreover, the experimental results show that our method is superior to the existing single-band and multispectral destriping methods. Also, we further use the algorithm to the stripe noise removal of other real remote sensing images, and excellent image quality is obtained, which proves the universality of the algorithm.<\/jats:p>","DOI":"10.3390\/rs11182098","type":"journal-article","created":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T04:12:40Z","timestamp":1568002360000},"page":"2098","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A Method for the Destriping of an Orbita Hyperspectral Image with Adaptive Moment Matching and Unidirectional Total Variation"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2602-9250","authenticated-orcid":false,"given":"Qingyang","family":"Li","sequence":"first","affiliation":[{"name":"Beijing Advanced Innovation Center for Imaging Theory and Technology, Capital Normal University, Beijing 100048, China"},{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application Ministry of Education, Capital Normal University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruofei","family":"Zhong","sequence":"additional","affiliation":[{"name":"Beijing Advanced Innovation Center for Imaging Theory and Technology, Capital Normal University, Beijing 100048, China"},{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Key Laboratory of 3D Information Acquisition and Application Ministry of Education, Capital Normal University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ya","family":"Wang","sequence":"additional","affiliation":[{"name":"The School of Information Engineering, Zunyi Normal University, Zunyi 563100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1109\/TGRS.2010.2081370","article-title":"Subspace-based striping noise reduction in hyperspectral images","volume":"49","author":"Acito","year":"2011","journal-title":"IEEE Trans. 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