Automatic Threshold Selection Using the Wavelet Transform

Abstract

A new method of peak analysis for threshold selection is presented. It is based on the wavelet transform which provides a multiscale analysis of the information content of the histogram of an image. We show that the detection of the zero-crossings and the local extrema of a wavelet transform of the histogram gives a complete characterization of the peaks in the histogram, that is to say, the values at which they start, end, and are extreme. These values are used for the unsupervised and automatic selection of a sequence of thresholds describing a coarse-to-fine analysis of histogram variation. The results of using the proposed technique are presented in the case of different images.