AUTOMATIC +1 DIFFRACTION ORDER DETECTION IN OFF-AXIS DIGITAL HOLOGRAPHIC INTERFEROMETRY USING AN ENERGY-BASED SPECTRAL MODEL

Authors

• Nigora Alimdjanovna Akbarova, Tashkent State Technical University named after Islam KarimovFollow
• Dilnoza Ibrokhim kizi Abdulkhayeva, Tashkent State Technical University named after Islam KarimovFollow

Abstract

This paper presents an automatic +1 diffraction order detection algorithm for off-axis digital holographic interferometry (DHI Manual spectral filtering is widely used to find out the desired order of diffraction in the Fourier domain in conventional digital holographic reconstruction. Nevertheless, this approach is very subjective and must be subject to expert guidance, thus, the reconstruction reproducibility and stability can often deteriorate. To address these limitations, this designed scheme constructs a spectral model utilizing energy-maximization as well as adaptive DC suppression and dynamic filter radius estimates. The algorithm itself can automatically observe the distribution of energy in the hologram spectrum and select the optimal region of the hologram for the +1 diffraction order. Data on the reconstruction operator is given as an analytical expression to describe the filtering and reconstruction process. The proposed algorithm was also validated against noise and spectral distortions. Based on quantitative and experimental tests, this method greatly enhances phase retrieval stabilization and deformation measurement capability in digital holographic interferometric systems. The method is applicable in non-contact optical metrology, surface deformation analysis, and precision measurement studies.

First Page

34

Last Page

39

References

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Recommended Citation

Akbarova, Nigora Alimdjanovna and Abdulkhayeva, Dilnoza Ibrokhim kizi (2026) "AUTOMATIC +1 DIFFRACTION ORDER DETECTION IN OFF-AXIS DIGITAL HOLOGRAPHIC INTERFEROMETRY USING AN ENERGY-BASED SPECTRAL MODEL," Technical science and innovation: Vol. 2026: Iss. 3, Article 6.
Available at: https://btstu.researchcommons.org/journal/vol2026/iss3/6