# JP3D compression of solar data-cubes: photospheric imaging and spectropolarimetry

## TL;DR

This paper evaluates the effectiveness of JP3D, a 3D wavelet-based compression standard, for lossless compression of various solar hyperspectral data-cubes, addressing storage and transfer challenges in solar physics observations.

## Contribution

It provides an assessment of JP3D's performance on different types of solar data-cubes, highlighting its suitability for lossless compression in solar physics.

## Key findings

- JP3D achieves high compression rates for solar data-cubes.
- Compression performance varies with data type and sampling.
- Lossless compression with JP3D is effective for solar hyperspectral data.

## Abstract

Hyperspectral imaging is an ubiquitous technique in solar physics observations and the recent advances in solar instrumentation enabled us to acquire and record data at an unprecedented rate. The huge amount of data which will be archived in the upcoming solar observatories press us to compress the data in order to reduce the storage space and transfer times. The correlation present over all dimensions, spatial, temporal and spectral, of solar data-sets suggests the use of a 3D base wavelet decomposition, to achieve higher compression rates. In this work, we evaluate the performance of the recent JPEG2000 Part 10 standard, known as JP3D, for the lossless compression of several types of solar data-cubes. We explore the differences in: a) The compressibility of broad-band or narrow-band time-sequence; I or V stokes profiles in spectropolarimetric data-sets; b) Compressing data in [x,y,$\lambda$] packages at different times or data in [x,y,t] packages of different wavelength; c) Compressing a single large data-cube or several smaller data-cubes; d) Compressing data which is under-sampled or super-sampled with respect to the diffraction cut-off.