Novel fusion method for SAR and optical images based on non-subsampled shearlet transform

Abstract

ABSTRACTDue to the different imaging modes of SAR images and optical images, traditional image fusion methods are no longer suitable for the fusion of the two types of images. Fused images often have problems of spectral distortion and excessive introduction of noise. This study proposes an improved SAR-optical images fusion algorithm based on non-subsampled shearlet transform (NSST). NSST decomposition is first performed on the two types of images. Then, in the low-frequency sub-band of the decomposition image, a weighted average fusion rule using the coefficient of variation according to the different imaging characteristics of SAR images and optical images is proposed to avoid spectral distortion. In the high-frequency sub-band of the decomposition image, the effect of SAR image noise on the fused image is removed by setting the coherence coefficient threshold. The subjective visual assessment and objective index evaluation on the experimental results both show that the fusion results using the proposed algorithm are significantly improved. The proposed algorithm smoothly fuses the detailed information of the SAR image into the optical image without the excessive introduction of noise while maintaining the spectral information of the optical image. Meanwhile, the proposed algorithm has a relatively simpler mathematical structure compared to the algorithm based on sparse representation, thus reducing the operating time and manual work.