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New Score-Based Turbo Message Passing Algorithm Enhances Compressive Imaging

Researchers have developed a new message-passing algorithm called Score-Based Turbo Message Passing (STMP) for compressive imaging. This method integrates score-based generative models with empirical Bayes denoising to improve image reconstruction, particularly in underdetermined scenarios. For systems with quantized measurements, a variant called Quantized STMP (Q-STMP) was also introduced, which includes a dequantization module and remains robust even with 1-bit quantization. Experiments show that STMP offers a better performance-complexity tradeoff than existing methods and typically converges within 10 iterations. AI

IMPACT This new algorithm could improve image reconstruction quality and efficiency in various imaging applications.

RANK_REASON The cluster contains a research paper detailing a new algorithm for compressive imaging. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.CV →

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New Score-Based Turbo Message Passing Algorithm Enhances Compressive Imaging

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The cluster contains a research paper detailing a new algorithm for compressive imaging. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Chang Cai, Hao Jiang, Xiaojun Yuan, Ying-Jun Angela Zhang ·

    Score-Based Turbo Message Passing for Plug-and-Play Compressive Imaging

    arXiv:2512.14435v2 Announce Type: replace Abstract: Message-passing algorithms have been adapted for compressive imaging by incorporating various off-the-shelf image denoisers. However, these denoisers rely largely on generic or hand-crafted priors and often fall short in accurat…