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Two large-exposure-ratio image fusion by improved morphological segmentation.

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    Area of Science:

    • Image processing
    • Computer vision
    • Aerospace engineering

    Background:

    • Image fusion of high-dynamic-range scenes, like rocket launches, is difficult due to motion and scene complexity.
    • Over-exposed areas in images can lead to halo artifacts during fusion.

    Purpose of the Study:

    • To develop a robust image fusion method for rocket launch imagery.
    • To mitigate halo artifacts caused by over-exposed regions.

    Main Methods:

    • Proposed a principle of halo formation in large-exposure-ratio images.
    • Developed an improved morphological segmentation (IMS) method to segment over-exposed regions and boundaries.
    • Implemented an improved multiscale fusion method incorporating segmentation of high-exposed images.
    • Utilized a two-camera simultaneous imaging system to capture dynamic rocket launch events.

    Main Results:

    • The proposed fusion method effectively preserves details and colors of rocket flames.
    • Subjective observations indicate superior visual quality compared to existing methods.
    • Objective metrics demonstrate enhanced edge and contrast performance.

    Conclusions:

    • The developed image fusion technique successfully addresses halo artifacts in rocket launch imagery.
    • The method offers significant improvements in preserving image details and color fidelity.
    • This approach enhances the observational quality of dynamic aerospace events.