An NSST-Based Fusion Method for Airborne Dual-Frequency, High-Spatial-Resolution SAR Images

With the continuous development of synthetic aperture radar (SAR) technology, SAR image data are becoming increasingly abundant. For same scene, dual-frequency (high-frequency and low-frequency) images can present different details feature information. fusion two frequencies combine advantages both, thus describing targets more comprehensively. Because high-resolution contain a large amount detailed information, such as edges textures, traditional methods cannot fuse this information better, resulting in loss To solve problem, article proposes method suitable for airborne dual-frequency, images. First, source decomposed to obtain their low-pass bands high-pass by using nonsubsampled Shearlet transform (NSST). Then, we apply improved nonnegative matrix factorization merge use new sum modified Laplacian bands. After that, fused reconstructed inverse NSST, final image. Finally, processing data, effectiveness proposed is verified.