Noise reduction in digital holography based on a filtering algorithm

Wenhui Zhang; Liangcai Cao; Hua Zhang; Guofan Jin; David Brady

doi:10.1117/12.2288729

23 February 2018 Noise reduction in digital holography based on a filtering algorithm

Wenhui Zhang, Liangcai Cao, Hua Zhang, Guofan Jin, David Brady

Author Affiliations +

Proceedings Volume 10503, Quantitative Phase Imaging IV; 105030H (2018) https://doi.org/10.1117/12.2288729
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

Holography is a tool to record the object wavefront by interference. Complex amplitude of the object wave is coded into a two dimensional hologram. Unfortunately, the conjugate wave and background wave would also appear at the object plane during reconstruction, as noise, which blurs the reconstructed object. From the perspective of wave, we propose a filtering algorithm to get a noise-reduced reconstruction. Due to the fact that the hologram is a kind of amplitude grating, three waves would appear when reconstruction, which are object wave, conjugate wave and background wave. The background is easy to eliminate by frequency domain filtering. The object wave and conjugate wave are signals to be dealt with. These two waves, as a whole, propagate in the space. However, when detected at the original object plane, the object wave would diffract into a sparse pattern while the conjugate wave would diffract into a diffused pattern forming the noise. Hence, the noise can be reduced based on these difference with a filtering algorithm. Both amplitude and phase distributions are truthfully retrieved in our simulation and experimental demonstration.

Citation Download Citation

Wenhui Zhang, Liangcai Cao, Hua Zhang, Guofan Jin, and David Brady "Noise reduction in digital holography based on a filtering algorithm", Proc. SPIE 10503, Quantitative Phase Imaging IV, 105030H (23 February 2018); https://doi.org/10.1117/12.2288729

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KEYWORDS

Holograms

Reconstruction algorithms

Holography

Digital holography

Optical filters

Denoising

Fourier transforms

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