Journal
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 70, Issue -, Pages 835-849Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2022.3147735
Keywords
Autocorrelation; Noise measurement; Signal to noise ratio; Rotation measurement; Extraterrestrial measurements; Q measurement; Photomicrography; Autocorrelation analysis; multi-target detection; cryo-electron microscopy
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Funding
- Yitzhak and Chaya Weinstein Research Institute for Signal Processing
- NSF-BSF [2019752]
- Zimin Institute for Engineering Solutions Advancing Better Lives, BSF [2020159]
- ISF [1924/21]
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The study addresses the multi-target detection problem by proposing a method for image recovery in high noise conditions, estimating the image through an autocorrelation analysis framework, and demonstrating accurate image recovery in high noise environments through extensive numerical experiments.
We consider thetwo-dimensional multi-target detection problem of recovering a target image from a noisy measurement that contains multiple copies of the image, each randomly rotated and translated. Motivated by the structure reconstruction problem in single-particle cryo-electron microscopy, we focus on the high noise regime, where the noise hampers accurate detection of the image occurrences. We develop an autocorrelation analysis framework to estimate the image directly from a measurement with an arbitrary spacing distribution of image occurrences, bypassing the estimation of individual locations and rotations. We conduct extensive numerical experiments, and demonstrate image recovery in highly noisy environments.(1)
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