New approach for applying high-order entropy coding to image data

Steve S. Yu; Nikolas P. Galatsanos

doi:10.1117/12.157920

22 October 1993 New approach for applying high-order entropy coding to image data

Steve S. Yu, Nikolas P. Galatsanos

Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.157920
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States

Abstract

Entropy coding is a well-known method for exploiting the statistical redundancy in order to compress image data. Information theory indicates that the coding efficiency can be improved by utilizing high-order entropy coding (HEC). However, due to the high complexity of the implementation and the difficulties in estimating the high-order statistics during the coding process, high-order entropy coding has not been widely used. Conditional coding of an Lth order Markov source requires 2^KL code tables with 2^K probabilities in each table. In this paper, we present a new approach called binary decomposed high-order entropy coding (BDHEC) that significantly reduces the complexity of implementation of HEC techniques. Furthermore, it increases the accuracy of estimating the statistical model and thus it also improves the effectiveness of HEC for practical applications. The novelty of this approach is that the K-bits, M equals 2^K representation levels, grayscale image is decomposed into M binary sub-images, each corresponding to one representation level of M outcomes of pels. Since each sub-image has only two representation levels, K is reduced to 1, the smallest possible value. Thus, when high-order conditional entropy coding is applied to these sub- images instead of the original image, the implementation complexity is significantly reduced and the accuracy of estimating the statistical model is increased. Theoretical analysis and experimental results are presented, which verify the value of BDHEC.

Citation Download Citation

Steve S. Yu and Nikolas P. Galatsanos "New approach for applying high-order entropy coding to image data", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.157920

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available