Regularized dequantizers for DCT-based transform coding of images

Gunho Lee; Sinae Kim; Samuel Moon-Ho Song

doi:10.1117/12.411864

29 December 2000 Regularized dequantizers for DCT-based transform coding of images

Gunho Lee, Sinae Kim, Samuel Moon-Ho Song

Proceedings Volume 4310, Visual Communications and Image Processing 2001; (2000) https://doi.org/10.1117/12.411864
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

We have recently proposed a new dequantization scheme for DCT- based transform coding based on regularization principles. The new approach sharply reduced blocking artifacts in decoded images and the performance of the new dequantization scheme has been evaluated against the standard JPEG, MPEG and H.263+ in terms of the peak-signal-to-noise ratio (PSNR) with our own definition of the blockiness measure (BM). Basically, the proposed dequantizer maps the received data to within the range +/- (quantizer spacing/2), so that the final decompressed image is 'smooth' in the sense of minimizing the cost functional including the stabilizing term weighted by a regularization parameter. In this paper, we focus on several important aspect of this regularized dequantizer, namely the selection of the regularization parameter and the convergence of the dequantization algorithm.

Citation Download Citation

Gunho Lee, Sinae Kim, and Samuel Moon-Ho Song "Regularized dequantizers for DCT-based transform coding of images", Proc. SPIE 4310, Visual Communications and Image Processing 2001, (29 December 2000); https://doi.org/10.1117/12.411864

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