In digital preservation, a common approach for preservation actions is the migration to standardized formats. Full validation of the results of such conversion processes is required to ensure authenticity and trust. This process of quality assurance is a key obstacle to achieving scalability for large volumes of content. In this article, we address the quality assurance process for the preservation of born-digital photographs and validate conversions of raw image formats into standard formats such as Adobe Digital Negative. To achieve this, we rely on a systematic planning framework. We classify requirements that have to be evaluated according to their measurement needs. We extend an existing measurement framework using a combination of tools, image similarity algorithms, and purpose-built plugins. By combining metadata extraction, image rendering and comparison, and perceptual-level quality assurance, we evaluate the feasibility of automating the core part of quality assurance that is often the most costly part of preservation processes.