Score-based diffusion priors for multi-target detection

Zabatani, Alon; Kreymer, Shay; Bendory, Tamir

doi:10.1109/ciss59072.2024.10480190

2024 58th Annual Conference on Information Sciences and Systems (CISS) 2024

DOI: 10.1109/ciss59072.2024.10480190

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Score-based diffusion priors for multi-target detection

Alon Zabatani,

Shay Kreymer,

Tamir Bendory

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Denoiser-Based Projections for 2D Super-Resolution MRA

Shani,

Tirer,

Giryes

et al. 2024

IEEE Open J. Signal Process.

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We study the 2D super-resolution multi-reference alignment (SR-MRA) problem: estimating an image from its down-sampled, circularly translated, and noisy copies. The SR-MRA problem serves as a mathematical abstraction of the structure determination problem for biological molecules. Since the SR-MRA problem is ill-posed without prior knowledge, accurate image estimation relies on designing priors that describe the statistics of the images of interest. In this work, we build on recent advances in image processing and harness the power of denoisers as priors for images. To estimate an image, we propose utilizing denoisers as projections and using them within two computational frameworks that we propose: projected expectation-maximization and projected method of moments. We provide an efficient GPU implementation and demonstrate the effectiveness of these algorithms through extensive numerical experiments on a wide range of parameters and images.

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Denoiser-Based Projections for 2D Super-Resolution MRA

Shani,

Tirer,

Giryes

et al. 2024

IEEE Open J. Signal Process.

Self Cite

View full text Add to dashboard Cite

show abstract

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Score-based diffusion priors for multi-target detection

Cited by 1 publication

References 24 publications

Denoiser-Based Projections for 2D Super-Resolution MRA

Denoiser-Based Projections for 2D Super-Resolution MRA

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