Hanning Li

Ms. Hanning Li


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 October 2026 in Applied Sciences
Verified
Journal Article
Open access
PDF file
YLYanchang Liu
Yanchang Liu
LSLiu Shuyi
Liu Shuyi
WZWeiyi Zhao
Weiyi Zhao
HLHanning Li
Hanning Li
奕廖奕婷 廖
奕婷 廖
YXyi fan Xu
yi fan Xu
Digital Rock Physics (DRP) requires high-fidelity pore-scale imaging, yet micro-computed tomography (μ-CT) trades spatial resolution against field of view, and standard super-resolution (SR) often fails to preserve transport-controlling pore topology. We propose Vision-LSTM and State-Space Super-Resolution (ViSSR), a physics-informed hybrid residual SR network that couples Vision-LSTM (ViL) for local anisotropic texture with a Mamba-based 2D selective state-space module (SS2D) for linear-complexity global context, and restores high-frequency structure via scale-conditioned residuals under an explicit partial-volume and PSF degradation model. Because reconstruction errors propagate into permeability and flow analysis, we report the pixel metrics PSNR, SSIM, and LPIPS together with topology-aware scores comprising pore-size-distribution earth mover’s distance (PSD-EMD; one-dimensional Wasserstein-1), porosity, connectivity, spanning, and fractal dimension. On DeepRock-SR, ViSSR attains 32.08 dB PSNR, 0.746 SSIM, and 0.04 PSD-EMD at ×4, and preserves pore topology across sandstone, carbonate, and coal where perceptual baselines hallucinate or oversmooth. Zero-shot slice-stacked reconstruction on independently acquired dual-resolution carbonates from MRCCM, project DRP-362, further yields volumetric transport gains over bicubic upsampling under scanner-realized ×4 degradation.