Inferring Galaxy Morphology Through Texture Analysis

We give an approach to estimate galaxy morphology from digital images. In particular, our algorithm extracts orientation information of the texture at difference scales and merges the multiscale information into an unified representation. By fitting a morphological model based on the textural information, we derived an quantitative and physically meaningful description of galaxy morphology. Such description will be useful for studying the evolution of galaxies.