By Topic

A study of vector transform coding of subband-decomposed images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Weiping Li ; Dept. of Comput. Sci. & Electr. Eng., Lehigh Univ., Bethlehem, PA, USA ; Ya-Qin Zhang

Studies vector transform coding (VTC), a new image coding scheme, on subband-decomposed images. It is shown that vector transformation (VT) reduces the inter-vector correlation, although not as much as the discrete cosine transform (DCT). However, it is also shown that VT preserves the intra-vector correlation much better than the DCT so that vector quantization (VQ) in the VT domain can be made more efficient. VTC of subband-decomposed images introduces another dimension of adaptivity, in which coding parameters, bit allocation, and VQ codebooks can be adapted to each level of the subband pyramid as well as to each vector in the VT domain. The new subband/VTC scheme is compared with VQ of original images, VQ of subband-decomposed images, DCT-based transform coding, and subband/DCT/VQ schemes. Simulation results indicate that the new scheme achieves 1 to 3dB improvement over the other schemes in terms of peak signal-to-noise ratio. This improvement is also supported by subjective evaluations

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:4 ,  Issue: 4 )