Multiscale Methods for Image Processing: The Wavelet and the Scale-Space Approaches

Abstract

Multiscale approaches have been largely considered in several signal processing applications. They play an important role when designing automatic methods to cope with real world measurements where, in most of the cases, there is no prior information about which would be the appropriate scale. The basic idea behind a multiscale analysis is to embed the original signal into a family of derived signals, thus allowing the analysis of different representation levels and, further, the choice of the ones exhibiting the interest features. This paper presents a brief survey of two broadly used multiscale formulations, namely, wavelets and scale-space filtering. We present the basic definitions and some possible applications of these approaches in image processing.