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A brain-inspired approach for SAR-to-optical image translation based on diffusion models.

Hao Shi^1,2,3, Zihan Cui^1,3, Liang Chen^1,3

¹Radar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing, China.

Frontiers in Neuroscience

|February 14, 2024

Summary

This study introduces a new diffusion model for translating Synthetic Aperture Radar (SAR) images into optical images. This advanced technique enhances Earth observation by making SAR data more interpretable for users.

Keywords:

SAR-to-optical image translation brain-inspired approach cognitive processes diffusion model synthetic aperture radar

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Area of Science:

Remote Sensing
Computer Vision
Artificial Intelligence

Background:

Synthetic Aperture Radar (SAR) is vital for all-weather, all-day Earth observation but lacks intuitive interpretation compared to optical imagery.
Bridging the interpretability gap between SAR and optical images is crucial for broader accessibility and application in Earth observation.

Purpose of the Study:

To develop a novel generative model for translating SAR images into optical images, aligning with human cognitive habits.
To enhance the feature extraction capabilities for improved SAR image interpretation and translation.

Main Methods:

A conditional image-to-image translation framework based on the diffusion model is proposed, inspired by human brain processing.
Enhanced feature extraction is achieved using self-attention and long-skip connection mechanisms.
A novel data augmentation strategy is employed to address the scarcity of SAR-optical image pairs, optimizing data efficiency.

Main Results:

The proposed method successfully translates SAR images to high-fidelity optical images.
The generated optical images exhibit clarity, avoiding blurriness, as demonstrated on the SAR2Opt dataset.

Conclusions:

The developed diffusion model framework offers a significant advancement in SAR to optical image translation.
This work facilitates more intuitive interpretation of SAR data, broadening its utility in Earth observation applications.