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.