Low-memory-usage image coding with line-based wavelet transform

Linning Ye; Jiangling Guo; Brian S. Nutter; Sunanda D. Mitra

doi:10.1117/1.3541802

1 February 2011 Low-memory-usage image coding with line-based wavelet transform

Linning Ye, Jiangling Guo, Brian S. Nutter, Sunanda D. Mitra

Author Affiliations +

Optical Engineering, Vol. 50, Issue 2, 027005 (February 2011). https://doi.org/10.1117/1.3541802

Abstract

When compared to the traditional row-column wavelet transform, the line-based wavelet transform can achieve significant memory savings. However, the design of an image codec using the line-based wavelet transform is an intricate task because of the irregular order in which the wavelet coefficients are generated. The independent block coding feature of JPEG2000 makes it work effectively with the line-based wavelet transform. However, with wavelet tree-based image codecs, such as set partitioning in hierarchical trees, the memory usage of the codecs does not realize significant advantage with the line-based wavelet transform because many wavelet coefficients must be buffered before the coding starts. In this paper, the line-based wavelet transform was utilized to facilitate backward coding of wavelet trees (BCWT). Although the BCWT algorithm is a wavelet tree-based algorithm, its coding order differs from that of the traditional wavelet tree-based algorithms, which allows the proposed line-based image codec to become more memory efficient than other line-based image codecs, including line-based JPEG2000, while still offering comparable rate distortion performance and much lower system complexity.

©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Linning Ye, Jiangling Guo, Brian S. Nutter, and Sunanda D. Mitra "Low-memory-usage image coding with line-based wavelet transform," Optical Engineering 50(2), 027005 (1 February 2011). https://doi.org/10.1117/1.3541802

Published: 1 February 2011

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