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Dynamic range compression and detail enhancement algorithm for infrared image.

Gang Sun, Songlin Liu, Weihua Wang

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    Summary
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    This study introduces a new algorithm for infrared images to improve dynamic range compression and detail enhancement (DRCDDE). The method effectively enhances dim targets and suppresses noise for better image display and detection.

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    Area of Science:

    • Image processing
    • Computer vision
    • Infrared imaging

    Background:

    • Traditional infrared imaging systems face challenges with high sampling widths and 8-bit data limitations.
    • Displaying and processing infrared images often requires managing a wide dynamic range and enhancing subtle details.

    Purpose of the Study:

    • To present a novel high dynamic range compression and detail enhancement (DRCDDE) algorithm for infrared images.
    • To address limitations in traditional display and real-time processing systems for infrared data.

    Main Methods:

    • Utilizing a bilateral filter to decompose infrared images into base and detail components.
    • Developing an operator model for dynamic range compression (DRC) with local contrast preservation and a nonlinear intensity transfer function (ITF).
    • Implementing adaptive DRC for the base component and detail enhancement with noise suppression for the detail component.

    Main Results:

    • The proposed DRCDDE algorithm demonstrates superior performance compared to existing methods on real infrared data.
    • Quantitative comparisons validate the effectiveness of the algorithm in enhancing image quality.
    • The algorithm successfully projects dim targets while effectively suppressing noise.

    Conclusions:

    • The developed DRCDDE algorithm offers significant improvements for infrared image processing.
    • This technique is beneficial for both enhancing image display and improving target detection capabilities in infrared systems.