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Sample Drift Correction Following 4D Confocal Time-lapse Imaging
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Optically coherent image formation and denoising using a plug and play inversion framework.

Casey J Pellizzari, Russell Trahan, Hanying Zhou

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    We developed a new framework for coherent imaging that effectively reduces noise using Gaussian denoising algorithms (GDAs). This method significantly improves image reconstruction accuracy compared to standard techniques.

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    Area of Science:

    • Optics
    • Image Processing
    • Signal Processing

    Background:

    • Optically coherent imaging systems face performance limitations due to measurement and speckle noise.
    • Speckle noise in coherent imaging is signal-dependent and follows an exponential distribution, posing challenges for traditional noise reduction methods.

    Purpose of the Study:

    • To develop an image formation framework for maximum a posteriori (MAP) estimation in coherent imaging.
    • To enable the use of Gaussian denoising algorithms (GDAs) for mitigating noise in coherent imaging without modification.
    • To compare the performance of various GDAs using simulated and experimental data.

    Main Methods:

    • Development of a novel image formation framework based on MAP estimation.
    • Application of unmodified Gaussian denoising algorithms (GDAs) to address noise in coherent imaging.
    • Comparative analysis of different GDAs using both simulated and experimental coherent imaging data.

    Main Results:

    • The proposed framework successfully mitigates exponentially distributed and signal-dependent noise.
    • Gaussian denoising algorithms (GDAs) can be directly applied within the new framework.
    • The framework demonstrates robustness to noise and significantly reduces reconstruction error compared to standard inversion methods.

    Conclusions:

    • The developed image formation framework enhances the performance of optically coherent imaging systems.
    • The framework provides a robust and effective method for noise reduction in coherent imaging.
    • This approach offers a significant improvement in image reconstruction accuracy for coherent imaging applications.