Block-based segmentation and adaptive coding for visually lossless compression of scanned documents

This paper presents a novel block-based segmentation and adaptive coding (BSAC) algorithm for visually lossless compression of scanned documents that contain not only photographic images but also text and graphic images. For such a compound image source, we structure the image into nonoverlapping blocks and classify each block into four different classes based on the empirical statistics within the block. Different coding strategies are applied to different classes in order to achieve the very best compression performance. Our new block-based image coder is able to provide visually lossless compression of scanned documents at the bit rate of around 1/spl sim/1.5 bpp with modest computational complexity and very low memory requirement.

[1]  Amir Said,et al.  Simplified segmentation for compound image compression , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[2]  Wenjun Zeng,et al.  An efficient color re-indexing scheme for palette-based compression , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[3]  Trac D. Tran,et al.  Optimizing block-thresholding segmentation for multilayer compression of compound images , 2000, IEEE Trans. Image Process..

[4]  Xin Li,et al.  On the study of lossless compression of computer generated compound images , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[5]  Yoshua Bengio,et al.  High quality document image compression with "DjVu" , 1998, J. Electronic Imaging.

[6]  Ricardo L. de Queiroz.  On Data-Filling Algorithms for MRC Layers , 2000, ICIP.

[7]  Steven Pigeon,et al.  Lossy compression of partially masked still images , 1998, Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225).

[8]  Hui Cheng,et al.  Document compression using rate-distortion optimized segmentation , 2001, J. Electronic Imaging.