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Toward Unaligned Guided Thermal Super-Resolution.

Honey Gupta, Kaushik Mitra

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |December 2, 2021
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    Summary

    This study introduces novel methods for super-resolving low-resolution thermal images using visible-light images without pixel-level alignment. These techniques improve thermal imaging accessibility by overcoming sensor cost limitations.

    Area of Science:

    • Computer Vision
    • Image Processing
    • Sensor Technology

    Background:

    • Thermography offers valuable imaging in low visibility but high-resolution sensors are costly.
    • Visible-light cameras often accompany thermal cameras, presenting an opportunity for guided super-resolution (GSR).
    • Spectral differences between thermal and visible images hinder pixel-wise alignment, limiting existing GSR methods.

    Purpose of the Study:

    • To develop novel guided super-resolution (GSR) models that do not require pixel-to-pixel alignment between thermal and visible images.
    • To enhance the applicability of thermal imaging by enabling super-resolution from readily available, unaligned image pairs.
    • To address the challenge of spectral misalignment in stereo thermal-visible image pairs for super-resolution tasks.

    Main Methods:

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    • Proposed two models for unaligned guided super-resolution (GSR): one using a correlation-based feature-alignment loss, and another incorporating a misalignment-map estimation block.
    • Developed an end-to-end framework for automatic alignment and super-resolution of unaligned thermal and visible image pairs.
    • Utilized a high-resolution visible-range camera as a guide to super-resolve low-resolution thermal images.

    Main Results:

    • Demonstrated that the proposed models effectively perform guided super-resolution (GSR) without requiring pixel-to-pixel alignment.
    • Experimental results show superior performance compared to existing single and guided super-resolution techniques for unaligned thermal images.
    • Validated the models' suitability for super-resolving very low-resolution thermal images using unaligned visible-light guidance.

    Conclusions:

    • The developed methods successfully remove the necessity of pixel-to-pixel alignment for guided super-resolution (GSR) of thermal images.
    • These approaches offer a practical solution for enhancing thermal imaging capabilities, making high-resolution thermal data more accessible.
    • The proposed models represent a significant advancement in unaligned guided super-resolution, particularly for low-resolution thermal imaging applications.