Polar Scale-Invariant Feature Transform for Synthetic Aperture Radar Image Registration

Abstract

Obtaining high accuracy in orientation assignment for Synthetic Aperture Radar (SAR) image registration is a great challenge because of the serious speckle noise and geometrical distortion. In this letter, a polar scale-invariant feature transform (PSIFT) descriptor is proposed for SAR image registration. The novel descriptor is invariant to rotation, skipping the dominant orientation assignment. In PSIFT, a polar-transformed support region is adopted to calculate the gradient magnitudes and orientations and further sampled in the radial and angular directions with different scales. The final descriptor is then built with the orientation bins covering the omnidirectional space. Furthermore, an improved dual-matching method is proposed to achieve sufficiently correct matches. Extensive experiments confirm that the PSIFT descriptor is suitable for SAR image registration because of its excellent performance.