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Related Experiment Video

Updated: Apr 27, 2026

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Pixel-based defect detection from high-NA optical projection images.

Dongbo Xu, Tim Fühner, Andreas Erdmann

    Applied Optics
    |July 1, 2014
    PubMed
    Summary

    This study reconstructs subwavelength defects in high numerical aperture (NA) projection systems using defect footprints. The method accurately determines defect position, shape, and transmission, even with noise.

    Area of Science:

    • Optics and Photonics
    • Metrology
    • Nanofabrication

    Background:

    • High numerical aperture (NA) projection systems are crucial for advanced lithography.
    • Accurate characterization of subwavelength defects in mask layouts is essential for yield improvement.
    • Existing methods may struggle with precise defect localization and parameter estimation.

    Purpose of the Study:

    • To demonstrate a novel technique for reconstructing subwavelength defects in high-NA projection systems.
    • To accurately determine the position, shape, and transmission of sparse, unknown defects within a known mask layout.
    • To analyze the impact of defect size and type on reconstruction accuracy and the technique's noise sensitivity.

    Main Methods:

    • Utilizing the 'defect footprint' (difference between images with and without defects) for reconstruction.

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  • Employing a cost function and optimization algorithms to analyze the defect footprint.
  • Simulating and measuring the performance with varying defect characteristics and noise levels.

    • Main Results:

    • Successful reconstruction of subwavelength defect position, shape, and transmission.
    • Demonstrated dependency of reconstruction accuracy on defect size and type.
    • Investigated and quantified the technique's sensitivity to noise in measured images.

    Conclusions:

    • The proposed defect reconstruction technique is effective for sparse, subwavelength defects in high-NA systems.
    • The method provides a robust approach for mask defect metrology.
    • Further research can explore applications in real-time defect analysis and process control.