A MULTISCALE VISION MODEL TO ANALYZE FIELD ASTRONOMICAL IMAGES

We have implemented a multiscale vision model based on the wavelet tra nsform to analyse field astronomical images. The discrete transform is performed by the a trous algorithm. The vision model is based oil the notion of significant structures. We identify the pixels of the assoc iated wavelet transform space (WTS) with the objects. For each scale i t region labelling is carried out. An interscale connectivity graph is then established. In accordance with some rules that permit false det ections to be removed, the objects and their sub-objects ale identifie d. They define respectively trees and sub-trees in the graph. In this way, the identification of the WTS pixels of the tree related to a giv en object leads to the reconstruction of its image by the conjugate gr adient method. The model has been tested successfully on simulated ima ges of stars and galaxies which allow us to show the capabilities of t he detection and restoration procedures of the model. Finally: tests o n real images show that one carl analyse complex structures better tha n with classical astronomical vision models.