Lossless compression of continuous-tone images by combined inter-bit-plane decorrelation and JBIG coding

Lossless compression techniques are essential in some applications, such as archival and communication of medical im- ages. In this paper, an improvement on the Joint Bi-Level Imaging Group (JBIG) method for continuous-tone image compression is proposed. The method is an innovative combination of multiple decorrelation procedures, namely a lossless Joint Photographic Ex- perts Group (JPEG)-based predictor, a transform-based inter-bit- plane decorrelator, and a JBIG-based intra-bit-plane decorrelator. The improved JBIG coding scheme outperformed lossless JPEG coding, JBIG coding, and the best mode of compression with revers- ible embedded wavelets (CREW) coding, on the average bit rate, by 0.56 (8 bits/component images only), 0.14, and 0.12 bits per pixel with the JPEG standard set of 23 continuous-tone test images. The compression technique may be easily incorporated into currently existing JBIG-based products. A high-order entropy estimation algo- rithm is also presented, which indicates the potentially achievable lower bound bit rate, and should be useful in decorrelation analysis as well as in the design as cascaded decorrelators. © 1997 SPIE and IS&T. (S1017-9909(97)00802-7)

[1]  Nasser M. Nasrabadi,et al.  Image coding using vector quantization: a review , 1988, IEEE Trans. Commun..

[2]  Kiyoharu Aizawa,et al.  Model-based image coding advanced video coding techniques for very low bit-rate applications , 1995, Proc. IEEE.

[3]  Xiaolin Wu,et al.  A segmentation-based predictive multiresolution image coder , 1995, IEEE Trans. Image Process..

[4]  Paul W. Melnychuck,et al.  Conditioning contexts for the arithmetic coding of bit planes , 1992, IEEE Trans. Signal Process..

[5]  Michel Barlaud,et al.  Image coding using wavelet transform , 1992, IEEE Trans. Image Process..

[6]  Rangaraj M. Rangayyan,et al.  Improved joint bilevel image experts group (JBIG) data compression of continuous-tone images , 1996, Other Conferences.

[7]  P. W. Jones,et al.  Digital Image Compression Techniques , 1991 .

[8]  Ahmad Zandi,et al.  CREW: Compression with Reversible Embedded Wavelets , 1995, Proceedings DCC '95 Data Compression Conference.

[9]  John W. Woods,et al.  Subband Image Coding , 1990 .

[10]  Tenkasi V. Ramabadran,et al.  The use of contextual information in the reversible compression of medical images , 1992, IEEE Trans. Medical Imaging.

[11]  G. Basharin On a Statistical Estimate for the Entropy of a Sequence of Independent Random Variables , 1959 .

[12]  T. K. Truong,et al.  Comparison of international standards for lossless still image compression , 1994, Proc. IEEE.

[13]  Simon Haykin,et al.  Neural network approaches to image compression , 1995, Proc. IEEE.

[14]  Rangaraj M. Rangayyan,et al.  Performance analysis of reversible image compression techniques for high-resolution digital teleradiology , 1992, IEEE Trans. Medical Imaging.

[15]  Ying Wang A set of transformations for lossless image compression , 1995, IEEE Trans. Image Process..

[16]  Manohar Das,et al.  Lossless compression of medical images using two-dimensional multiplicative autoregressive models , 1993, IEEE Trans. Medical Imaging.

[17]  Nikolas P. Galatsanos,et al.  Lossless compression of multi-dimensional medical image data using binary-decomposed high-order entropy coding , 1994, Proceedings of 1st International Conference on Image Processing.

[18]  Christodoulos Chamzas,et al.  Technical features of the JBIG standard for progressive bi-level image compression , 1992, Signal Process. Image Commun..

[19]  Gregory K. Wallace,et al.  The JPEG still picture compression standard , 1991, CACM.

[20]  Rangaraj M. Rangayyan,et al.  Segmentation-based lossless coding of medical images , 1995, Other Conferences.