{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T01:47:09Z","timestamp":1768009629118,"version":"3.49.0"},"reference-count":49,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T00:00:00Z","timestamp":1734393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Development Program of Jilin Province, China","award":["20240212002GX"],"award-info":[{"award-number":["20240212002GX"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Color distortion is a common issue in Jilin-1 KF01 series satellite imagery, a phenomenon caused by the instability of the sensor during the imaging process. In this paper, we propose a data-driven method to correct color distortion in Jilin-1 KF01 imagery. Our method involves three key aspects: color-distortion simulation, model design, and post-processing refinement. First, we investigate the causes of color distortion and propose algorithms to simulate this phenomenon. By superimposing simulated color-distortion patterns onto clean images, we construct color-distortion datasets comprising a large number of paired images (distorted\u2013clean) for model training. Next, we analyze the principles behind a denoising model and explore its feasibility for color-distortion correction. Based on this analysis, we train the denoising model from scratch using the color-distortion datasets and successfully adapt it to the task of color-distortion correction in Jilin-1 KF01 imagery. Finally, we propose a novel post-processing algorithm to remove boundary artifacts caused by block-wise image processing, ensuring consistency and quality across the entire image. Experimental results show that the proposed method significantly eliminates color distortion and enhances the radiometric quality of Jilin-1 KF01 series satellite imagery, offering a solution for improving its usability in remote sensing applications.<\/jats:p>","DOI":"10.3390\/rs16244721","type":"journal-article","created":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T10:54:02Z","timestamp":1734432842000},"page":"4721","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Color-Distortion Correction for Jilin-1 KF01 Series Satellite Imagery Using a Data-Driven Method"],"prefix":"10.3390","volume":"16","author":[{"given":"Jiangpeng","family":"Li","sequence":"first","affiliation":[{"name":"Chang Guang Satellite Technology Co., Ltd., Changchun 130000, China"}]},{"given":"Yang","family":"Bai","sequence":"additional","affiliation":[{"name":"Chang Guang Satellite Technology Co., Ltd., Changchun 130000, China"}]},{"given":"Shuai","family":"Huang","sequence":"additional","affiliation":[{"name":"Chang Guang Satellite Technology Co., Ltd., Changchun 130000, China"}]},{"given":"Song","family":"Yang","sequence":"additional","affiliation":[{"name":"Chang Guang Satellite Technology Co., Ltd., Changchun 130000, China"}]},{"given":"Yingshan","family":"Sun","sequence":"additional","affiliation":[{"name":"Chang Guang Satellite Technology Co., Ltd., Changchun 130000, China"}]},{"given":"Xiaojie","family":"Yang","sequence":"additional","affiliation":[{"name":"Chang Guang Satellite Technology Co., Ltd., Changchun 130000, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,17]]},"reference":[{"key":"ref_1","first-page":"112","article-title":"Multi-and hyperspectral geologic remote sensing: A review","volume":"14","author":"Hecker","year":"2012","journal-title":"Int. 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