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IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Mengxin Gong1, Jie Li2, Mengqian Chen2

  • 1Information and Communication Engineering, Xi'an Jiaotong University, Xi'an, 710049, China; Ningbo Jiuzhang Zhitong Technology, Ningbo, Zhejiang, 315207, China.

Neural Networks : the Official Journal of the International Neural Network Society
|June 30, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an illumination-guided network for fusing intensity and polarization images. The method enhances visual perception by preserving photometric consistency and object details, improving target detection.

Keywords:
IlluminationImage fusionPolarization imageSaliency injection

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Area of Science:

  • Computer Vision
  • Image Processing
  • Optics

Background:

  • Intensity images (S0) capture scene radiance, while Degree of Linear Polarization (DoLP) reveals material properties.
  • Effective fusion of S0 and DoLP enhances visual perception but is challenging under complex illumination.
  • Existing methods often fail to maintain photometric consistency and saliency during fusion, causing artifacts.

Purpose of the Study:

  • To develop a novel fusion method that addresses the limitations of existing polarization image fusion techniques.
  • To improve robustness and accuracy in visual perception, especially under complex lighting conditions.
  • To enhance downstream tasks like target detection through improved image fusion.

Main Methods:

  • Proposed an illumination-guided frequency-decoupled fusion network (IGFD-Net).
  • Introduced an illumination-guided attention mechanism to dynamically weight S0 and DoLP based on illumination priors.
  • Implemented a frequency-decoupled fusion module for visual naturalness and a structure-aware saliency injection loss for photometric consistency.

Main Results:

  • The IGFD-Net achieved competitive performance in subjective and objective image quality assessments.
  • The method demonstrated superior ability in maintaining photometric consistency and preserving structural details compared to existing approaches.
  • Fusion results showed improved accuracy in downstream target detection tasks.

Conclusions:

  • The proposed IGFD-Net effectively fuses intensity and polarization images, overcoming limitations of prior methods.
  • The illumination-guided and frequency-decoupled approach ensures robust visual perception and naturalness.
  • This method offers significant improvements for applications requiring accurate visual information extraction and analysis.