Lossy Compression of Integer Astronomical Images Preserving Photometric Properties*

Abstract Observatories are producing astronomical image data at quickly increasing rates. As a result, the efficiency of the compression methods employed is critical to meet the storage and distribution requirements of both observatories and scientists. This paper presents a novel lossy compression technique that is able to preserve the results of photometry analysis with high fidelity while improving upon the state of the art in terms of compression performance. The proposed compression pipeline combines a flexible bi-region quantization scheme with the lossless, dictionary-based, LPAQ9M encoder. The quantization process allows compression performance and photometric fidelity to be precisely tailored to different scientific requirements. A representative data set of 16-bit integer astronomical images produced by telescopes from all around the world has been employed to empirically assess its compression-fidelity trade-offs, and compare them to those of the de facto standard Fpack compressor. In these experiments, the widespread SExtractor software is employed as the ground truth for photometric analysis. Results indicate that after lossy compression with our proposed method, the decompressed data allows consistent detection of over 99% of all astronomical objects for all tested telescopes, maintaining the highest photometric fidelity (as compared to state of the art lossy techniques). When compared to the best configuration of Fpack (Hcompress lossy using 1 quantization parameter) at similar compression rates, our proposed method provides better photometry precision: 7.15% more objects are detected with magnitude errors below 0.01, and 9.13% more objects with magnitudes below SExtractor’s estimated measurement error. Compared to the best lossless compression results, the proposed pipeline allows us to reduce the compressed data set volume by up to 38.75% and 27.94% while maintaining 90% and 95%, respectively, of the detected objects with magnitude differences lower than 0.01 mag; and up to 18.93% while maintaining 90% of the detected objects with magnitude differences lower than the photometric measure error.

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Publication Details

Journal
Publications of the Astronomical Society of the Pacific
Published
2024-11-01
DOI
https://doi.org/10.1088/1538-3873/ad8b69
Primary Topic
Advanced Data Compression Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Lossy Compression of Integer Astronomical Images Preserving Photometric Properties*

Òscar Maireles-González, Joan Bartrina-Rapestà, Miguel Hernández-Cabronero, Joan Serra-Sagristà
Publications of the Astronomical Society of the Pacific
Advanced Data Compression Techniques
article

Lossy Compression of Integer Astronomical Images Preserving Photometric Properties*

Òscar Maireles-González, Joan Bartrina-Rapestà, Miguel Hernández-Cabronero, Joan Serra-Sagristà
article en

Abstract

Abstract Observatories are producing astronomical image data at quickly increasing rates. As a result, the efficiency of the compression methods employed is critical to meet the storage and distribution requirements of both observatories and scientists. This paper presents a novel lossy compression technique that is able to preserve the results of photometry analysis with high fidelity while improving upon the state of the art in terms of compression performance. The proposed compression pipeline combines a flexible bi-region quantization scheme with the lossless, dictionary-based, LPAQ9M encoder. The quantization process allows compression performance and photometric fidelity to be precisely tailored to different scientific requirements. A representative data set of 16-bit integer astronomical images produced by telescopes from all around the world has been employed to empirically assess its compression-fidelity trade-offs, and compare them to those of the de facto standard Fpack compressor. In these experiments, the widespread SExtractor software is employed as the ground truth for photometric analysis. Results indicate that after lossy compression with our proposed method, the decompressed data allows consistent detection of over 99% of all astronomical objects for all tested telescopes, maintaining the highest photometric fidelity (as compared to state of the art lossy techniques). When compared to the best configuration of Fpack (Hcompress lossy using 1 quantization parameter) at similar compression rates, our proposed method provides better photometry precision: 7.15% more objects are detected with magnitude errors below 0.01, and 9.13% more objects with magnitudes below SExtractor’s estimated measurement error. Compared to the best lossless compression results, the proposed pipeline allows us to reduce the compressed data set volume by up to 38.75% and 27.94% while maintaining 90% and 95%, respectively, of the detected objects with magnitude differences lower than 0.01 mag; and up to 18.93% while maintaining 90% of the detected objects with magnitude differences lower than the photometric measure error.

Publications of the Astronomical Society of the PacificVol. 136(11)
Universitat Autònoma de Barcelona (ES)
Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya, Ministerio de Ciencia e Innovación, Instituto de Astrofísica de Canarias, European Regional Development Fund, Agencia Estatal de Investigación, Integrated Electronics Engineering Center, Binghamton University
Openalex Percentile: Top 80%
Advanced Data Compression Techniques
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