A denoising method for phase-retrieval-based imaging

Shuyue Zhu; Wenjun Yi; Meicheng Fu; Junli Qi; Mengjun Zhu; Xiujian Li

doi:10.1117/12.2667772

27 February 2023 A denoising method for phase-retrieval-based imaging

Shuyue Zhu, Wenjun Yi, Meicheng Fu, Junli Qi, Mengjun Zhu, Xiujian Li

Proceedings Volume 12585, International Conference on Precision Instruments and Optical Engineering (PIOE 2022); 125850E (2023) https://doi.org/10.1117/12.2667772
Event: International Conference on Precision Instruments and Optical Engineering (PIOE 2022), 2022, Guangzhou, China

Abstract

Denoising is significant in many fields, especially for computational imaging. Coherent diffraction imaging and speckle correlation imaging are regarded as the most promising computational imaging techniques. The above two imaging techniques can be classified as phase-retrieval-based imaging due to the phase-retrieval is a vital procedure for object reconstruction. However, the acquisition process would generate unavoidable noise and participate in the iteration process of phase-retrieval. Hence, it is necessary to denoising after obtained the original reconstruction image. Here, a denoising method that based on connected domain is proposed for phase-retrieval method. We experimentally demonstrate the denoising results and quantitatively analyze the effect. Comparison of the classical median filter, wiener filter and bilateral filter, our method shows a satisfactory denoising effect. Our results prove that connected domain denoising is useful and promising, which provides a new post-processing denoising method for phase-retrieval-based imaging.

Citation Download Citation

Shuyue Zhu, Wenjun Yi, Meicheng Fu, Junli Qi, Mengjun Zhu, and Xiujian Li "A denoising method for phase-retrieval-based imaging", Proc. SPIE 12585, International Conference on Precision Instruments and Optical Engineering (PIOE 2022), 125850E (27 February 2023); https://doi.org/10.1117/12.2667772

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