DOAJ Open Access 2023

Fourier Ptychography Reconstruction Based on Reweighted Amplitude Flow With Regularization by Denoising and Deep Decoder

Baopeng Li Caiwen Ma Okan K. Ersoy Zhibin Pan Wansha Wen +2 lainnya

Abstrak

Fourier ptychography (FP) is a computational imaging technique with the advantage that it can obtain large field-of-view (FOV) and high-resolution (HR) imaging. We propose an algorithm for Fourier ptychography based on reweighted amplitude flow (RAF) with regularization by denoising (RED) and deep decoder (DD), which is an untrained deep generative model. The proposed method includes two loops, using reweighted amplitude flow with regularization by denoising as an inner loop for phase retrieval and deep decoder for further denoising as an outer loop in the Fourier ptychography recovery system. The proposed method does not need any training dataset, just adds a little computer time during the image recovery process. The proposed method has no bias due to training images, which is different from other deep learning methods. The experimental results show that the proposed method can improve the reconstruction quality in both PSNR and SSIM.

Topik & Kata Kunci

Applied optics. Photonics Optics. Light

Penulis (7)

Baopeng Li

Caiwen Ma

Okan K. Ersoy

Zhibin Pan

Wansha Wen

Zhonghan Sun

Wei Gao

Format Sitasi

APA MLA BibTeX

Li, B., Ma, C., Ersoy, O.K., Pan, Z., Wen, W., Sun, Z. et al. (2023). Fourier Ptychography Reconstruction Based on Reweighted Amplitude Flow With Regularization by Denoising and Deep Decoder. https://doi.org/10.1109/JPHOT.2022.3230422

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.1109/JPHOT.2022.3230422
Akses: Open Access ✓