Novel object-oriented video coder employing correlation-maximizing extrapolation

Jun-Seo Lee; Seung-Seok Oh; Rin-Chul Kim; Sang Uk Lee

doi:10.1117/12.386652

30 May 2000 Novel object-oriented video coder employing correlation-maximizing extrapolation

Jun-Seo Lee, Seung-Seok Oh, Rin-Chul Kim, Sang Uk Lee

Proceedings Volume 4067, Visual Communications and Image Processing 2000; (2000) https://doi.org/10.1117/12.386652
Event: Visual Communications and Image Processing 2000, 2000, Perth, Australia

Abstract

In this paper, the performance of the extrapolation block transform (EBT) and the shape-adaptive DCT (SA-DCT) for arbitrarily shaped image segment coding is theoretically compared. The comparison indicates that the EBT approach yields better performance than the SA-DCT on the highly correlated image at low bit rates. Since the correlation maximizing extrapolation (CME) algorithm proposed in maximizes the correlation of the extrapolated block, it is considered to be one of the EBT techniques that can achieve the performance expected by the theoretical performance. Thus, a novel object-oriented video coder employing the CME algorithm for the texture coding is proposed in this paper, and its performance is compared with that of the MPEG-4 VM through intensive computer simulations. In the proposed video coder, the contour coding technique employing the two- stage motion compensation is adopted for the shape coding, and the rate-constrained hierarchical grid interpolation is adopted for the object-based motion compensation. The simulation results show that the proposed coder outperforms the MPEG-4 VM by about 0.84 approximately 1.29 dB depending on the test sequences at the same bit rate.

Citation Download Citation

Jun-Seo Lee, Seung-Seok Oh, Rin-Chul Kim, and Sang Uk Lee "Novel object-oriented video coder employing correlation-maximizing extrapolation", Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); https://doi.org/10.1117/12.386652

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