TY - GEN
T1 - Single-Shot Fractional Fourier Phase Retrieval
AU - Yang, Yixiao
AU - Tao, Ran
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Traditional phase retrieval is generally concerned with re-covering a signal from its Fourier magnitude measurements whose inherent ambiguities make this problem especially difficult. In this work, we present an efficient phase retrieval technique from the single fractional Fourier transform (FrFT) magnitude measurement. Specifically, the FrFT measurement can be well-combined with signal priors via a generalized alternating projection framework, which can effectively alleviate the ambiguities of phase retrieval and the stagnation problem of numerical iterative processes. Through numerical simulations, we demonstrate that reconstructing an image from the single FrFT measurement leads to a significant performance improvement over that from the Fourier transform magnitude by using the proposed method. The source code is available at https://github.com/Yixiao-Yang/SFrFPR.
AB - Traditional phase retrieval is generally concerned with re-covering a signal from its Fourier magnitude measurements whose inherent ambiguities make this problem especially difficult. In this work, we present an efficient phase retrieval technique from the single fractional Fourier transform (FrFT) magnitude measurement. Specifically, the FrFT measurement can be well-combined with signal priors via a generalized alternating projection framework, which can effectively alleviate the ambiguities of phase retrieval and the stagnation problem of numerical iterative processes. Through numerical simulations, we demonstrate that reconstructing an image from the single FrFT measurement leads to a significant performance improvement over that from the Fourier transform magnitude by using the proposed method. The source code is available at https://github.com/Yixiao-Yang/SFrFPR.
KW - Phase retrieval
KW - fractional Fourier transform
KW - generalized alternating projection
KW - single-shot
UR - http://www.scopus.com/inward/record.url?scp=85177592263&partnerID=8YFLogxK
U2 - 10.1109/ICASSP49357.2023.10095976
DO - 10.1109/ICASSP49357.2023.10095976
M3 - Conference contribution
AN - SCOPUS:85177592263
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
BT - ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Y2 - 4 June 2023 through 10 June 2023
ER -