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Semantic description and annotation of digital images is the key to management and reusing of images in humanities computing. Due to the lack of domain-specific hierarchical description schema and controlled vocabulary for digital images, annotation results produced by current methods such as machine annotation based on low-level visual features of images, and human annotation based on expert's experiences,have the problem of low quality and inconsistency. To solve this problem,we propose a semantic description framework for the content description based on information needs and retrieval theory. The framework combines a semantic description framework and a domain thesaurus. In this paper, we elaborate on the relationship between semantic levels under this description framework. Then, we conduct a preliminary test with this method in the cultural heritage field using the Dunhuang fresco digital image. 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.