New vector transform for image coding

Shipeng Li; Weiping Li

doi:10.1117/12.233243

27 February 1996 New vector transform for image coding

Shipeng Li, Weiping Li

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233243
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

Vector quantization (VQ) always outperforms scalar quantization. Recently, vector transform coding (VTC) has been introduced to better take advantage of signal processing for vector quantization and shown to achieve better performance in image coding. How much performance advantage in terms of rate-distortion can a vector transform coding scheme gain over the other coding schemes? What is the optimal vector transform (VT) with complexity constraint on VQ? These are the questions we try to answer in this paper. Based on the results from high-resolution or asymptotic (in rate) quantization theory, we obtain a general rate- distortion formula for signal processing combined with vector quantization for first-order Gaussian-Markov source. We prove that VTC indeed has better performance than other existing coding schemes with the same or less complexity based on the rate-distortion measurement. A new mirror-sampling based vector transform which only involves additions and subtractions is proposed. For high rate case, we show that the new VTC scheme achieves the optimal performance under the complexity constraint. A 2D version of the new vector transform is applied to image coding, and the results show that the new vector transform consistently outperforms the subsampling-based vector transform.

Citation Download Citation

Shipeng Li and Weiping Li "New vector transform for image coding", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233243

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