MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-Resolution

TL;DR

This paper introduces MuS2, a new real-world benchmark for multi-image super-resolution of Sentinel-2 satellite images, providing a standardized evaluation procedure to advance research in this area.

Contribution

The paper presents MuS2, the first real-world benchmark for Sentinel-2 super-resolution, including an end-to-end evaluation protocol and use of WorldView-2 imagery as high-resolution reference.

Findings

First real-world benchmark for Sentinel-2 super-resolution

Provides an end-to-end evaluation procedure

Facilitates advancement in multi-image super-resolution research

Abstract

Insufficient image spatial resolution is a serious limitation in many practical scenarios, especially when acquiring images at a finer scale is infeasible or brings higher costs. This is inherent to remote sensing, including Sentinel-2 satellite images that are available free of charge at a high revisit frequency, but whose spatial resolution is limited to 10 m ground sampling distance. The resolution can be increased with super-resolution algorithms, in particular when performed from multiple images captured at subsequent revisits of a satellite, taking advantage of information fusion that leads to enhanced reconstruction accuracy. One of the obstacles in multi-image super-resolution consists in the scarcity of real-world benchmarks - commonly, simulated data are exploited which do not fully reflect the operating conditions. In this paper, we introduce a new MuS2 benchmark for super-resolving multiple Sentinel-2 images, with WorldView-2 imagery used as the high-resolution reference. Within MuS2, we publish the first end-to-end evaluation procedure for this problem which we expect to help the researchers in advancing the state of the art in multi-image super-resolution.