日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細

登録内容を編集ファイル形式で保存
 
 
ダウンロード電子メール
  On Variational Problem with Nonstandard Growth Conditions for the Restoration of Clouds Corrupted Satellite Images

Khanenko, P., Kogut, P., & Uvarov, M. (2022). On Variational Problem with Nonstandard Growth Conditions for the Restoration of Clouds Corrupted Satellite Images. In CITRisk 2021 Computational & Information Technologies for Risk-Informed Systems 2021 Proceedings of the 2nd International Workshop on Computational & Information Technologies for Risk-Informed Systems (CITRisk 2021) co-located with XXI International Conference on Information Technologies in Education and Management (ITEM 2021) Kherson, Ukraine, September 16-17, 2021. CEUR workshop proceedings; 3101 (pp. 6-25). Technical University of Aachen. Retrieved from http://ceur-ws.org/Vol-3101/Paper1.pdf.

Item is

基本情報

表示: 非表示:
アイテムのパーマリンク: https://hdl.handle.net/21.11116/0000-000A-A8D0-D 版のパーマリンク: https://hdl.handle.net/21.11116/0000-000B-2301-C
資料種別: 会議論文

ファイル

表示: ファイル

関連URL

表示:

作成者

表示:
非表示:
 作成者:
Khanenko, Pavel1, 著者           
Kogut, P.I.2, 著者
Uvarov, M.1, 著者
所属:
1Physics of Quantum Materials, Max Planck Institute for Chemical Physics of Solids, Max Planck Society, ou_1863462              
2External Organizations, ou_persistent22              

内容説明

表示:
非表示:
キーワード: Geometrical optics; Meteorology; Remote sensing; Restoration; Satellites, Information loss; Monitoring applications; Nonstandard growth conditions; Optical image; Optical remote sensing; Risk of cloud distortion of satellite image; Risk of information loss; Satellite images; Variational approaches; Variational problems, Image reconstruction
 要旨: Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. Typically, the optical satellite images are often corrupted because of poor weather conditions. As a rule, the measure of degradation of optical images is such that one can not rely even on the brightness inside of the damaged regions. As a result, some subdomains of such images become absolutely invisible. So, there is a risk of information loss in optical remote sensing data. In view of this, we propose a new variational approach for exact restoration of multispectral satellite optical images. We discuss the consistency of the proposed variational model, give the scheme for its regularization, derive the corresponding optimality system, and discuss the algorithm for the practical implementation of the reconstruction procedure. Experimental results are very promising and they show a significant gain over baseline methods using the reconstruction through linear interpolation between data available at temporally-close time instants. © 2021 Copyright for this paper by its authors.

資料詳細

表示:
非表示:
言語: eng - English
 日付: 2022-03-072022-03-07
 出版の状態: 出版
 ページ: -
 出版情報: -
 目次: -
 査読: -
 識別子(DOI, ISBNなど): URI: http://ceur-ws.org/Vol-3101/Paper1.pdf
 学位: -

関連イベント

表示:

訴訟

表示:

Project information

表示:

出版物 1

表示:
非表示:
出版物名: CITRisk 2021 Computational & Information Technologies for Risk-Informed Systems 2021 Proceedings of the 2nd International Workshop on Computational & Information Technologies for Risk-Informed Systems (CITRisk 2021) co-located with XXI International Conference on Information Technologies in Education and Management (ITEM 2021) Kherson, Ukraine, September 16-17, 2021. CEUR workshop proceedings ; 3101
種別: 会議論文集
 著者・編者:
所属:
出版社, 出版地: Technical University of Aachen
ページ: - 巻号: 3101 通巻号: - 開始・終了ページ: 6 - 25 識別子(ISBN, ISSN, DOIなど): ISSN: 1613-0073