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Related Experiment Videos

An Underwater Polarization Image Fusion Algorithm Based on Information Entropy and a Hierarchical-Adaptive Fusion

Fuqiang Wang1, Wei He1, Shanwei Ye1

  • 1School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.

Sensors (Basel, Switzerland)
|May 27, 2026
PubMed
Summary

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Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)01:15

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) is an advanced Nuclear Magnetic Resonance (NMR) technique specifically designed to detect and enhance the signals of low-abundance nuclei, such as carbon-13 and nitrogen-15, in small molecules. The fundamental principle behind INEPT is the transfer of polarization from a more abundant and highly polarizable nucleus, typically hydrogen-1, to the low-abundance nucleus of interest. This process effectively boosts the NMR signal of the...

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This study introduces a novel polarization image fusion method using information entropy and hierarchical fusion to enhance underwater images. The technique effectively reduces noise and sharpens details, improving visual analysis in aquatic environments.

Area of Science:

  • Computer Vision
  • Optical Engineering
  • Image Processing

Background:

  • Underwater images suffer from low contrast and lost details due to light scattering and absorption.
  • Polarization imaging mitigates these issues by reducing backscatter and improving contrast.

Purpose of the Study:

  • To propose a polarization image fusion method for enhanced underwater image quality.
  • To improve detail preservation and adaptive enhancement in challenging aquatic visual conditions.

Main Methods:

  • A polarization image fusion method guided by information entropy and a hierarchical-adaptive strategy.
  • Multiscale denoising of Degree of Linear Polarization (DOLP) images using local information entropy.
  • Hierarchical fusion incorporating detail injection for low-frequency components and structure-guided fusion for high-frequency components.
Keywords:
Gaussian decompositionimage fusioninformation entropyunderwater image enhancement

Related Experiment Videos

Main Results:

  • The method significantly improved objective metrics like information entropy, average gradient, and edge strength.
  • Experimental results on diverse datasets confirmed effective detail preservation and scene adaptability.
  • Ablation studies validated the framework's balance between detail enhancement and computational efficiency.

Conclusions:

  • The proposed polarization image fusion method offers a practical solution for underwater image enhancement.
  • The approach demonstrates potential for applications in underwater target detection and infrastructure inspection.