Abstract-In this work, a subband domain textual image compression method is developed. The document image is first decomposed into subimages using binary subband decompositions. Next, the character locations in the subbands and the symbol library consisting of the character images are encoded. The method is suitable for keyword search in the compressed data. It is observed that very high compression ratios are obtained with this method. Simulation studies are presented. Index Terms-Binary image coding, binary subband decomposition, document retrieval, textual image compression. Efficient compression of binary textual images is an important problem in many applications such as document archives and digital libraries. A textual image typically consists of repeated patterns that are mostly characters and punctuation marks. Exploiting the redundancy of character repetitions is the key feature of the document image coding algorithms [2]- [7] , which identify the locations of the characters in the image and replace them by pointers into a codebook of characters. The main steps of a typical textual image compression (TIC) method can be summarized as follows. 1) Find and extract a character in the image. 2) Compare it with the symbol library consisting of the separate character images. 3) If the character exists in the symbol library, take the location only, otherwise add it to the library. 4) Compress the constructed library and the symbol locations. 5) A further step is proposed by Witten et al. [6] who encode the residue image so that lossless compression can be achieved. In this paper, a subband domain textual image compression method is developed. The method consists of two stages as shown in Fig. 1 . In the first stage, the document image is decomposed into subimages using a binary subband decomposition structure. The second stage of the algorithm consists of encoding the repetitions of the character images in the subband domain. In Section II, binary subband decomposition methods are reviewed. Encoding of the subband character images is described in Section III and it is experimentally observed that the subband domain method produces higher compression results than regular methods. Furthermore, the computational cost of encoding Manuscript received March 14, 1997; revised December 14, 1998. This work was supported by the Turkish Scientific and Technical Research Council BDP program and the National Science Foundation under Grant INT-9406954. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Christine Podilchuk. O. N. Gerek was with Bilkent University, TR-06533 Bilkent, Ankara, Turkey. He is now with the Signal Processing Laboratory, Swiss Federal Institute of Technology, CH-1015 Ecublens, Switzerland (e-mail: gerek@ltssun2.epfl.ch), on leave from Anadolu University, Eskişehir, Turkey. A. E.Çetin is with the
Gerek et al. REF proposed a subband domain textual image compression method based on [2] .
Subband Domain Coding of Binary Textual Images for Document Archiving
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Computer Science Medicine