Image compression in local helioseismology

TL;DR

This paper evaluates how various lossy data compression techniques impact the accuracy of local helioseismology measurements, demonstrating robustness of key signals even with significant data reduction.

Contribution

It provides a comprehensive analysis of the effects of different lossy compression methods on helioseismic data, highlighting effective strategies for data reduction in space missions.

Findings

Helioseismic measurements are robust to lossy compression.

JPEG compression on subsampled data yields optimal results.

Time-distance helioseismology remains feasible with minimal data quality loss.

Abstract

Context. Several upcoming helioseismology space missions are very limited in telemetry and will have to perform extensive data compression. This requires the development of new methods of data compression. Aims. We give an overview of the influence of lossy data compression on local helioseismology. We investigate the effects of several lossy compression methods (quantization, JPEG compression, and smoothing and subsampling) on power spectra and time-distance measurements of supergranulation flows at disk center. Methods. We applied different compression methods to tracked and remapped Dopplergrams obtained by the Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory. We determined the signal-to-noise ratio of the travel times computed from the compressed data as a function of the compression efficiency. Results. The basic helioseismic measurements that we consider are very robust to lossy data compression. Even if only the sign of the velocity is used, time-distance helioseismology is still possible. We achieve the best results by applying JPEG compression on spatially subsampled data. However, our conclusions are only valid for supergranulation flows at disk center and may not be valid for all helioseismology applications.