Semantic description and annotation of digital images is key to the management and reuse of images in humanities computing. Due to the lack of domain-specific hierarchical description schema and controlled vocabularies for digital images, annotation results produced by current methods, such as machine annotation based on low-level visual features and human annotation based on experts’ experiences, are inconsistent and of poor quality. To solve this problem, we propose a semantic description framework for content description, based on information needs and retrieval theory. The framework combines the semantic description with a domain thesaurus. In this paper we describe the relationship between the semantic levels under this description framework. We conduct a preliminary test with this method in the cultural heritage field using digital images of the Dunhuang frescoes. We discuss the effect of semantic granularity on the annotation cost, from the point view of image semantic description granularity, and control strategies for an image’s semantic description quality. Our findings show that this framework is applicable to the description of cultural digital image content.