Recursive biorthogonal wavelet transform for image coding

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