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  1. Home
  2. Frequency-oriented Transformer For Remote Sensing Image Dehazing.
  1. Home
  2. Frequency-oriented Transformer For Remote Sensing Image Dehazing.

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Frequency-Oriented Transformer for Remote Sensing Image Dehazing.

Yaoqing Zhang1, Xin He1, Chunxia Zhan1

  • 1School of Basic Sciences for Aviation, Naval Aviation University, Yantai 264001, China.

Sensors (Basel, Switzerland)
|June 27, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces FOTformer, a novel frequency-oriented Transformer for remote sensing dehazing. It enhances image restoration by leveraging frequency domain analysis, outperforming existing methods.

Keywords:
fast Fourier transformfrequency domainimage restorationremote sensing image dehazing

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Area of Science:

  • Computer Vision
  • Remote Sensing Image Processing
  • Signal Processing

Background:

  • Remote sensing images suffer from haze, degrading visual task performance.
  • Existing dehazing methods often overlook frequency domain characteristics, limiting their representational capacity.

Purpose of the Study:

  • To propose a frequency-oriented Transformer (FOTformer) for effective remote sensing image dehazing.
  • To explore the frequency domain for improved haze removal and image restoration.

Main Methods:

  • Developed a frequency-prompt attention evaluator for frequency domain feature self-correlation.
  • Proposed a content reconstruction feed-forward network integrating global frequency and local spatial information.
  • Designed a spatial-frequency aggregation block for feature fusion between domains.

Main Results:

  • FOTformer demonstrates competitive performance on benchmark datasets.
  • The frequency-oriented approach significantly improves image restoration quality.
  • The proposed components effectively address haze degradation in remote sensing imagery.

Conclusions:

  • FOTformer offers a superior approach to remote sensing dehazing by utilizing frequency domain information.
  • The method effectively reconstructs global content and preserves multi-scale spatial details.
  • This work highlights the potential of frequency domain analysis in remote sensing image enhancement.