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    Area of Science:

    • Optics and Wave Propagation
    • Fluid Dynamics and Turbulence
    • Image Processing and Reconstruction

    Background:

    • Turbulent atmospheres significantly degrade imagery, posing challenges for accurate data acquisition and analysis.
    • Existing methods for recovering turbulence-corrupted data have limitations in performance and applicability.
    • Understanding the interplay between photon density and wave phase is crucial for advanced imaging.

    Purpose of the Study:

    • To introduce a new theoretical model for turbulence-corrupted imagery based on optimal mass transport.
    • To develop novel methods for reconstructing photon density flow affected by atmospheric turbulence.
    • To validate the model's efficacy using both coherent and incoherent imaging techniques.

    Main Methods:

    • Formulation of a new model integrating optimal mass transport theory with photon density and traveling wave phase.
    • Incorporation of a least action principle to derive the governing equations for photon density flow.
    • Experimental validation using coherent and incoherent imagery, comparing performance against established methods.

    Main Results:

    • The proposed optimal mass transport model accurately describes the relationship between photon density and wave phase.
    • The model facilitates approximate recovery of photon density flow in turbulent atmospheric conditions.
    • Superior performance was demonstrated in describing experimental data compared to existing techniques.

    Conclusions:

    • The new model offers a robust framework for understanding and mitigating turbulence effects in imagery.
    • The findings suggest a new class of algorithms for atmospheric imaging and wave propagation applications.
    • The model's effectiveness in experimental data validates its potential for practical use.