Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products

TL;DR

This paper introduces a novel parallax estimation method for push-frame satellite imagery, enabling improved super-resolution and 3D surface modeling from Skysat data by accounting for elevation-induced apparent motion.

Contribution

The paper presents a new linear Plane+Parallax decomposition combined with a multi-frame optical flow algorithm tailored for satellite image bursts with elevation changes.

Findings

Effective parallax estimation improves super-resolution results.

Estimated displacements assist in coarse 3D surface modeling.

Method handles scenes with significant elevation variation.

Abstract

Recent constellations of satellites, including the Skysat constellation, are able to acquire bursts of images. This new acquisition mode allows for modern image restoration techniques, including multi-frame super-resolution. As the satellite moves during the acquisition of the burst, elevation changes in the scene translate into noticeable parallax. This parallax hinders the results of the restoration. To cope with this issue, we propose a novel parallax estimation method. The method is composed of a linear Plane+Parallax decomposition of the apparent motion and a multi-frame optical flow algorithm that exploits all frames simultaneously. Using SkySat L1A images, we show that the estimated per-pixel displacements are important for applying multi-frame super-resolution on scenes containing elevation changes and that can also be used to estimate a coarse 3D surface model.