A general systematic method for the detection and segmentation of bright ta
rgets is developed in this paper. We use the term "bright target" to mean a
connected, cohesive object which has an average intensity distribution abo
ve that of the rest of the image. We develop an analytic model for the segm
entation of targets, which uses a novel multiresolution analysis in concert
with a Bayes classifier to identify the possible target areas. A method is
developed which adaptively chooses thresholds to segment targets from back
ground, by using a multiscale analysis of the image probability density fun
ction (PDF), A performance analysis based on a Gaussian distribution model
is used to show that the obtained adaptive threshold is often close to the
Bayes threshold. The method has proven robust even when the image distribut
ion is unknown. Examples are presented to demonstrate the efficiency of the
technique on a variety of targets.