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New RCL-Mamba model enhances image restoration for rapid 3D scanning

By PulseAugur Editorial · [1 sources] ·

Researchers have developed RCL-Mamba, a novel dual-domain State Space Model designed to improve image restoration for Rotational Scanning Computed Laminography (RCL). This method addresses rotational blur in projection data and sparse artifacts in image reconstructions, common issues in rapid non-destructive testing. By employing a cascaded joint processing strategy and a Mamba-CNN dual-branch module, RCL-Mamba effectively corrects blur and suppresses artifacts while preserving fine details. Evaluations show it significantly outperforms existing methods and can reduce scanning views by up to 8-fold without quality degradation, enhancing inspection efficiency for components like printed circuit boards. AI

IMPACT This research offers a more efficient and accurate method for 3D imaging in industrial inspection, potentially speeding up quality control processes.

RANK_REASON Academic paper detailing a new model and its application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New RCL-Mamba model enhances image restoration for rapid 3D scanning

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Academic paper detailing a new model and its application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xuyang Duan, Genyuan Zhang, Zhenjiang Dong, Chuandong Tan, Zihao Wang, Junyao Wang, Fenglin Liu ·

    RCL-Mamba: A Dual-domain State Space Model for Measurement-oriented Image Restoration in Rotational Sparse-View Scanning Computed Laminography

    arXiv:2606.31353v2 Announce Type: replace Abstract: Rotational Scanning Computed Laminography (RCL) is widely utilized for the Non-Destructive Testing (NDT) of large planar components. However, to facilitate rapid inspection, continuous sparse-view scanning is often employed, whe…

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