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Remote sensing super-resolution (RSSR) aims to improve remote sensing (RS) image resolution while providing finer spatial details, which is of great significance for high-quality RS image interpretation. The traditional RSSR is based on the optimization method, which pays insufficient attention to small targets and lacks the ability of model understanding and detail supplement. To alleviate the above problems, we propose the generative Diffusion Model with Detail Complement (DMDC) for RS super-resolution. Firstly, unlike traditional optimization models with insufficient image understanding, we introduce the diffusion model as a generation model into RSSR tasks and regard low-resolution images as condition information to guide image generation. Next, considering that generative models may not be able to accurately recover specific small objects and complex scenes, we propose the detail supplement task to improve the recovery ability of DMDC. Finally, the strong diversity of the diffusion model makes it possibly inappropriate in RSSR, for this purpose, we come up with joint pixel constraint loss and denoise loss to optimize the direction of inverse diffusion. The extensive qualitative and quantitative experiments demonstrate the superiority of our method in RSSR with small and dense targets. Moreover, the results from direct transfer to different datasets also prove the superior generalization ability of DMDC.

Seawater-based concrete has been increasingly employed in offshore construction engineering, especially where the construction materials and freshwater are inconvenient to access. In this paper, a full-field compressive deformation evaluation scheme was constructed by introducing the digital image correlation (DIC) technique in the uniaxial compression test for four kinds of seawater concrete fabricated by ordinary Portland cement (OPC) and calcium aluminate cement (CAC) when cured in freshwater and seawater conditions for 28 days, respectively. Digital speckle image sequences of the decorated concrete samples were simultaneously recorded during the compression test process, and thus, displacement fields of concrete cubes were mathematically obtained by way of correlation registration algorithms. On this basis, the normal strain, shear strain, and volumetric strain fields all over the front surface of the concrete samples were calculated with the aid of strain window method. In addition, compressive load-induced cracks were quantitatively tracked from the volumetric strain data. Subsequently, the full-field deformation-aided volumetric strain histogram percentage was computed to comparatively evaluate the failure behavior of four groups of seawater concretes. It was revealed that both the OPC and CAC-based seawater concretes gained enhanced strength under the seawater curing condition, but the OPC-S exhibited larger and more concentrated local deformation compared with OPC-F whereas the deformation of CAC-S was adversely widely spread in comparison with CAC-F.