DFFNet: 単一遠隔センサー画像解凍のためのダブルドメイン機能融合ネットワーク
Huazhong Jin1,2, Zhang Chen1, Zhina Song1,2
1School of Computer and Information Engineering, Hubei University of Technology, Wuhan 430068, China.
Sensors (Basel, Switzerland)
|August 28, 2025
まとめ
この研究では,遠隔検知画像の消毒を改善するためのダブルドメイン機能融合ネットワーク (DFFNet) が導入されます. ネットワークは,画像の詳細を復元しながら,大気中の霧を効果的に除去し,困難な条件下でパフォーマンスを向上させます.
科学分野:
- リモートセンシング
- コンピュータ・ビジョン
- 画像処理
背景:
- リモートセンシング画像の単一のデハジングは,下流のタスクに不可欠です.
- 従来の方法は不均一な霧と細部復元に苦労します.
- 大気中の散乱は 画像の質を著しく低下させる
研究 の 目的:
- 単一のリモートセンシング画像デハージングのための効果的な方法を提案する.
- ハーズ除去と細部修復のバランスをとる既存のアプローチの限界に対処する.
- リモートセンシング画像解析の性能を向上させるため
主な方法:
- 周波数復元ユニット (FRU) とコンテキスト抽出ユニット (CEU) を含むデュアルドメイン機能融合ネットワーク (DFFNet) を開発した.
- FRUは低周波の振幅を適応的に調節し,周波数領域のハズを抑制します.
- CEUは,文脈的な情報と詳細な再構築のガイドラインのために,複数のスケールの空間特性を抽出します.
- FRUとCEUの機能を融合させるための注意メカニズムを備えたダブルドメイン機能融合モジュール (DDFFM) を統合した.
主要な成果:
- DFFNetは画像全体に 効果的なハズ抑制を証明した.
- ネットワークは 濃い霧で薄められた 細部を再現しました
- StateHaze1k,RICE,RRSHIDのデータセットでの実験結果は,競争力のあるパフォーマンスを示しました.
- 既存の方法と比較して優れた視覚的品質と定量的な指標を達成しました.
結論:
- DFFNetは単一のリモートセンシング画像デハージングのための堅牢なソリューションを提供します.
- ダブルドメインのアプローチは 霧の除去と細部保存のバランスを取ります
- 提案された方法は,リモートセンシングの画像強化の最先端を大幅に進めている.
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