The significance of data acquisition in archaeological practice has consistently held great importance. Over the past few decades, the growing prevalence of digitization in acquiring data has significantly transformed the landscape of archaeological fieldwork, influencing both methodology and interpretation. The integration of digital photogrammetry and laser scanning technologies in archaeology has transformed data acquisition, enabling efficient and precise documentation. However, this digital shift raises concerns about information overload, the potential loss of on-site insights, and the need for suitable data management methods. Over the past 15 years, digital tools like photogrammetry, laser scanning, and unmanned aerial vehicles have advanced cultural heritage documentation. These methods offer detailed 3D models of archaeological sites, artifacts, and monuments, with evolving accessibility and user friendliness. This paper delves into methods for documenting cultural heritage, examining the implications of various approaches on the archaeologist’s workflow and on the field as a whole.

Current Multi-View Stereo (MVS) algorithms are tools for high-quality 3D model reconstruction, strongly depending on image spatial resolution. In this context, the combination of image Super-Resolution (SR) with image-based 3D reconstruction is turning into an interesting research topic in photogrammetry, around which however only a few works have been reported so far in the literature. Here, a thorough study is carried out on various state-of-the-art image SR techniques to evaluate the suitability of such an approach in terms of its inclusion in the 3D reconstruction process. Deep-learning techniques are tested here on a UAV image dataset, while the MVS task is then performed via the Agisoft Metashape photogrammetric tool. The data under experimentation are oblique cultural heritage imagery. According to results, point clouds from low-resolution images present quality inferior to those from upsampled high-resolution ones. The SR techniques HAT and DRLN outperform bicubic interpolation, yielding high precision/recall scores for the differences of reconstructed 3D point clouds from the reference surface. The current study indicates spatial image resolution increased by SR techniques may indeed be advantageous for state-of-the art photogrammetric 3D reconstruction.