Analysis and selection of coefficient feature by curvelet transform for SAR images

Synthetic aperture radar (SAR) imaging is very sensitive to direction, so if the information is obtained from multi-directions, it must be more accurate and more particular than that obtained from single direction. The Curvelet transform is a kind of multi-scale and multi-direction signal processing theory, and it is fit for SAR image decomposition. Moreover, it can extract each decomposed scale coefficient in light of demand. This paper mainly discusses the selection, reorganization and fusion of each scale coefficient for SAR image decomposed by Curvelet theory.