Speckle reduction of SAR images using curvelet and wavelet transforms based on spatial features characteristics

Synthetic Aperture Radar (SAR) satellite sensors recently provide valuable sources of earth observation data for various environmental applications. Beside the specifics properties of these data including multi-polarization and polarimetric image data, the presence of unavoidable speckle seriously degrades the quality of these data. Specifically, in certain applications such as clustering, classification and change detection speckles make some difficulties in analysis data and interpretation of results. In this research, a hybrid approach, based on frequency-domain transforms, is proposed. This method is a combination of wavelet and curvelet transforms to suppress the speckle noise in SAR images. This approach based on features and region which has a good efficiency in removing noise and preserving information of data in case of edges and shape. Results of these methods were compared simultaneously and with conventional speckle filtering methods (e.g. Lee, Frost and Kuan).