Towards building a Crowd-Sourced Sky Map

TL;DR

This paper presents a scalable system that combines uncalibrated, non-linearly transformed images from the web to create a high dynamic-range, wide-angle sky map, enabling new astronomical discoveries and scientific analysis.

Contribution

The authors introduce a novel pixel-rank based method for combining large sets of uncalibrated images, facilitating the creation of detailed sky maps from diverse, non-linear visual data.

Findings

Successfully combined web images into a high dynamic-range sky map

Discovered astronomical features not visible in individual images

Enabled scientific analysis of large, uncalibrated image datasets

Abstract

We describe a system that builds a high dynamic-range and wide-angle image of the night sky by combining a large set of input images. The method makes use of pixel-rank information in the individual input images to improve a "consensus" pixel rank in the combined image. Because it only makes use of ranks and the complexity of the algorithm is linear in the number of images, the method is useful for large sets of uncalibrated images that might have undergone unknown non-linear tone mapping transformations for visualization or aesthetic reasons. We apply the method to images of the night sky (of unknown provenance) discovered on the Web. The method permits discovery of astronomical objects or features that are not visible in any of the input images taken individually. More importantly, however, it permits scientific exploitation of a huge source of astronomical images that would not be available to astronomical research without our automatic system.