Recursive biorthogonal wavelet transform for image coding

Author

Feauveau, J.C. ; Mathieu, P. ; Barlaud, M. ; Antonini, M.

Author_Institution

LTIS, St. Quentin en Yvelines, France

fYear

1991

fDate

14-17 Apr 1991

Firstpage

2649

Abstract

A new method is proposed for image coding involving two steps. First, the authors use a dual recursive wavelet transform in order to obtain a set of subclasses of images with better characteristics than the original image (lower entropy, edges discrimination, etc.). Secondly, according to Shannon´s rate distortion theory, the wavelet coefficients are vector quantized. The purpose of this work is to present and study new recursive filter banks with perfect reconstruction as an alternative to FIR (finite impulse response) filters which are commonly used in wavelet analysis. The authors present two kinds of experimental results: coding of the well known Lena image with only two multiplications per pixel and then with an optimized IIR (infinite impulse response) filter

Keywords

data compression; digital filters; encoding; filtering and prediction theory; picture processing; IIR filter; Lena image; Shannon rate distortion theory; dual recursive wavelet transform; edges discrimination; entropy; image coding; infinite impulse response; perfect reconstruction; recursive biorthogonal wavelet transform; recursive filter banks; vector quantisation; wavelet coefficients; Entropy; Filter bank; Finite impulse response filter; IIR filters; Image coding; Image reconstruction; Rate distortion theory; Wavelet analysis; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on

Conference_Location

Toronto, Ont.

ISSN

1520-6149

Print_ISBN

0-7803-0003-3

Type

conf

DOI

10.1109/ICASSP.1991.150946

Filename

150946