Keyblock, which is a new framework we proposed for content-based image retrieval, is a generalization of the textbased information retrieval technology in the image domain. In this framework, keyblocks, which are analogous to keywords in text document retrieval, can be constructed by exploiting the method of Vector Quantization (VQ). Then an image can be represented as a list of keyblocks similar to a text document which can be considered as a list of keywords. Based on this image representation, various feature models can be constructed for supporting image retrieval. In this paper, we present a new feature representation model which use the keyblock-keyblock correlation matrix, termed keyblock-thesaurus, to facilitate the image retrieval. The feature vectors of this new model incorporate the effect of correlation between keyblocks, thus being more effective in representing image content.