Title :
Image coding using wavelet transform and classified vector quantisation
Author :
Lin, S. ; Salari, E.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Toledo Univ., OH, USA
fDate :
10/1/1996 12:00:00 AM
Abstract :
The wavelet transform, which provides a multiresolution representation of images, has been widely used in image compression. A new image coding scheme using the wavelet transform and classified vector quantisation is presented. The input image is first decomposed into a hierarchy of three layers containing ten subimages by the discrete wavelet transform. The lowest resolution low frequency subimage is scalar quantised with 8 bits/pixel. The high frequency subimages are compressed by classified vector quantisation to utilise the crosscorrelation among different resolutions while reducing the edge distortion and computational complexity. Vectors are constructed by combining the corresponding wavelet coefficients of different resolutions in the same orientation and classified according to the magnitude and the position of wavelet transform coefficients. Simulation results show that the proposed scheme has a better performance than those utilising current scalar or vector quantisation schemes
Keywords :
computational complexity; correlation methods; edge detection; image coding; image representation; image resolution; transform coding; vector quantisation; wavelet transforms; classified vector quantisation; computational complexity reduction; crosscorrelation; discrete wavelet transform; edge distortion reduction; high frequency subimages; image coding; image compression; image resolution; input image; low frequency subimage; multiresolution representation; performance; scalar quantised image; simulation results; vectors; wavelet coefficients;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:19960592