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Regularization techniques for 3D surface reconstruction from four quadrant backscattered electron detector images.

Matteo Giardino1, Devanarayanan Meena Narayana Menon2, Davide Luca Janner1

  • 1Department of Applied Science and Technology (DISAT), Politecnico di Torino, Corso Duca Degli Abruzzi 24, Torino, 10129, Italy; RU INSTM, Politecnico di Torino, Corso Duca Degli Abruzzi 24, Torino, 10129, Italy.

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Summary

Regularization techniques improve 3D surface reconstruction in scanning electron microscopy (SEM). This method enhances image quality by reducing artifacts from four quadrants backscattered electron detector (FQBSD) noise and alignment issues.

Keywords:
Backscattered electronsScanning electron microscopySurface reconstructionSurface regularization

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Area of Science:

  • Materials Science
  • Microscopy
  • Image Processing

Background:

  • Scanning electron microscopy (SEM) utilizes a four quadrants backscattered electron detector (FQBSD) for 3D surface reconstruction.
  • Integrating gradient fields from FQBSD signals is challenging due to electronic noise and detector variations.
  • Least squares integration is a common but limited approach for surface reconstruction.

Purpose of the Study:

  • To explore the application of regularization techniques for improved 3D surface reconstruction from FQBSD images.
  • To reduce distortions caused by detector sensitivity variations and misalignment in FQBSD systems.
  • To enhance the resolution and minimize artifacts in SEM-based 3D surface reconstructions.

Main Methods:

  • Implementation of Tikhonov's and Dirichlet's regularization techniques.
  • Application of these methods to reconstruct 3D surfaces from FQBSD data.
  • Experimental validation on various material samples.

Main Results:

  • Regularization techniques significantly reduce distortions and artifacts in 3D surface reconstruction.
  • Improved resolution and overall quality of reconstructed surfaces were observed.
  • Successful validation on AISI 316L stainless steel, aluminum, and silicon samples.

Conclusions:

  • Tikhonov's and Dirichlet's regularization offer a substantial improvement for 3D surface reconstruction using FQBSD.
  • These methods provide a more robust and accurate approach compared to traditional least squares integration.
  • The validated techniques show promise for advanced surface analysis in materials science.