High-quality rock CT reconstruction is essential for digital rock physics, yet recovering fine pore–fracture structures under limited spatial resolution remains challenging. This study proposes KAMSR, a Kernel-Sharing Adaptive Modulation Super-Resolution framework that integrates Kernel-Sharing Residual Blocks with Adaptive Modulation Layers (AML) to restore high-frequency details while suppressing artifacts at low parameter cost. Through partial Conv3×3 kernel sharing across cascaded residual-dense units, the default $\times 4$ generator contains only 4.66 M parameters, approximately $3.6\times$ smaller than typical RRDBNet-based SOTA models (≈16.7 M). Experiments on carbonate, coal, and sandstone CT datasets show that KAMSR outperforms competing super-resolution methods. Averaged over the three lithologies at $\times 4$ upscaling, it achieves a PSNR of 31.43 dB, an SSIM of 0.934, an LPIPS of 0.187, and an NIQE of 3.04. The reconstructions exhibit sharper pore boundaries, clearer mineral textures, and fewer artifacts, providing a more reliable basis for downstream digital-rock analyses.

Digital Rock Physics (DRP) requires high-fidelity pore-scale imaging, yet micro-computed tomography ($\mu$-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 $\times 4$, 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 $\times 4$ degradation.