A NEW WAVELET-BASED APPROACH TO PROGRESSIVE ENCODING OF REGIONS OF INTEREST IN A DIGITAL SIGNAL

Abstract

Progressive digital signal encoding and subsequent transmission refer to signal compression techniques that allow both the original signal reconstruction without loss of any detail and the construction of signal approximations (estimates) with the accuracy level depending on the amount of data available. Locally progressive encoding and transmission can be achieved by first transmitting a “rough” estimate of the original signal, then sending further details related to one or another selected block (region of interest - ROI) of the signal. In this paper, we propose a new wavelet-based approach to implementing of a locally progressive digital signal coding idea. The proposed approach explores both the newly developed fast procedures for evaluation of the discrete wavelet (Haar, LeGall) transform for particular selected ROI in the digital signal and the zero-tree-based encoders with an improved zero-tree analysis scheme.