By Topic

Performance comparison of two-dimensional discrete wavelet transform computation schedules on a VLIW digital signal processor

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 $31
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

3 Author(s)
Masselos, K. ; Dept. of Electr. & Electron. Eng., Imperial Coll., London, UK ; Andreopoulos, Y. ; Stouraitis, T.

The two-dimensional discrete wavelet transform (2D DWT) is becoming one of the standard tools for image and video compression systems. Various input-traversal schedules have been proposed for its computation. Here, major schedules for 2D DWT computation are compared with respect to their performance on a very long instruction-word (VLIW) digital signal processor (DSP). In particular, three popular transform-production schedules are considered: the row-column, the line based and the block based. Realisations of the wavelet transform according to the considered schedules have been developed. They are parameterised with respect to filter pair, image size and number of decomposition levels. All realisations have been mapped on a VLIW DSP, as these processors currently form an attractive alternative for the realisation of signal, image and video processing systems. Performance metrics for the realisations for a complete set of parameters have been obtained and compared. The experimental results show that each realisation performs better for different points of the parameter space.

Published in:

Vision, Image and Signal Processing, IEE Proceedings -  (Volume:153 ,  Issue: 2 )