Jigsaw-puzzle vector quantization for image compression

Chia-Hung Yeh

doi:10.1117/1.1633777

1 February 2004 Jigsaw-puzzle vector quantization for image compression

Chia-Hung Yeh

Optical Engineering, Vol. 43, Issue 2, (February 2004). https://doi.org/10.1117/1.1633777

A new finite-state vector quantization scheme called jigsaw-puzzle vector quantization (JPVQ) is proposed to provide better image quality, especially in the low bit rate context. For low bit rate image coding with conventional finite-state vector quantization (FSVQ) techniques, image quality degrades due to error propagation from one state to the next. The proposed JPVQ algorithm exploits the four-step side-match prediction technique to optimize the spatial continuity of each encoded block to improve the coding performance and reduce the error propagation effect. In the proposed coding scheme, an input block can be encoded by the jigsaw-puzzle block, the dynamic codebook, or the supercodebook. It is demonstrated with experimental results that JPVQ performs significantly better than traditional FSVQ techniques.

©(2004) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Chia-Hung Yeh "Jigsaw-puzzle vector quantization for image compression," Optical Engineering 43(2), (1 February 2004). https://doi.org/10.1117/1.1633777

Published: 1 February 2004

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