High-order entropy coding of medical image data using different binary-decomposed representations

Steve S. Yu; Miles N. Wernick; Nikolas P. Galatsanos

doi:10.1117/12.216786

18 August 1995 High-order entropy coding of medical image data using different binary-decomposed representations

Steve S. Yu, Miles N. Wernick, Nikolas P. Galatsanos

Proceedings Volume 2622, Optical Engineering Midwest '95; (1995) https://doi.org/10.1117/12.216786
Event: Optical Engineering Midwest '95, 1995, Chicago, IL, United States

Abstract

Information theory indicates that coding efficiency can be improved by utilizing high-order coding (HOEC). However, serious implementation difficulties limit the practical value of HOEC for grayscale image compression. In this paper we present a new approach, called binary-decomposed high-order entropy coding, that signifucantly reduces the complexity of the implementation and increases the accuracy in estimating the statistical model. In this appraoch a grayscale image is first decomposed into a group of binary sub-images. When HOEC is applied to these sub-images instead of the original image, the subsequent coding is made simpler and more accurate statistically. We apply this coding technique in lossless compression of medical images and imaging data, and demonstrate that the performance advantage of this approach is significant.

Citation Download Citation

Steve S. Yu, Miles N. Wernick, and Nikolas P. Galatsanos "High-order entropy coding of medical image data using different binary-decomposed representations", Proc. SPIE 2622, Optical Engineering Midwest '95, (18 August 1995); https://doi.org/10.1117/12.216786

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