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    This study introduces adaptive singular value decomposition ghost imaging (A-SVD GI), a dual-mode system for high-quality imaging and direct edge detection. It efficiently captures images with fewer samples by focusing illumination on foreground regions.

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    Area of Science:

    • Optics and Photonics
    • Computational Imaging
    • Image Processing

    Background:

    • Ghost imaging techniques traditionally require high sampling ratios for image reconstruction.
    • Adaptive imaging methods aim to improve efficiency by focusing on relevant image regions.
    • Singular Value Decomposition (SVD) offers a powerful tool for image analysis and pattern generation.

    Purpose of the Study:

    • To develop a dual-mode ghost imaging system capable of both high-quality imaging and direct edge detection.
    • To enhance sampling efficiency by adaptively illuminating only foreground regions.
    • To enable direct object edge revelation without prior image knowledge.

    Main Methods:

    • Implementation of adaptive singular value decomposition ghost imaging (A-SVD GI) with a threshold-based foreground pixel localization.
    • Switching between imaging and edge detection modes by adjusting foreground pixel selection range.
    • Utilizing binarized SVD patterns modulated by a digital micromirror device (DMD) for accelerated data acquisition.
    • Development of a single-round scheme to reduce measurement numbers.

    Main Results:

    • High-quality image retrieval at reduced sampling ratios using the imaging mode.
    • Direct and accurate object edge detection without requiring the original image.
    • Demonstration of dual-mode functionality through numerical simulations and experimental validation.
    • Significant speed-up in data acquisition via DMD modulation and single-round scheme.

    Conclusions:

    • The proposed A-SVD GI system offers a versatile and efficient solution for both imaging and edge detection.
    • The adaptive foreground illumination significantly reduces sampling requirements.
    • The dual-mode capability and accelerated acquisition make it suitable for real-time applications.
    • Potential for extension to multi-modality functional imaging and detection in fields like remote sensing and target recognition.