Efficient compression of binary textual images is very important for applications such as document archiving and retrieval, digital libraries and facsimile. The basic property of a textual image is the repetitions of small character images and curves inside the document. Exploiting the redundancy of these repetitions is the key step in most of the coding algorithms. In this paper, we use a similar compression method in subband domain. Four different subband decomposition schemes are described and their performances on textual image compression algorithm is examined. Experimentally, it is found that the described methods accomplish high compression ratios and they are suitable for fast database access and keyword search.