Lossy Compression of Integer Astronomical Images Preserving Photometric Properties
Maireles-González, Òscar (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Bartrina Rapesta, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Hernández-Cabronero, Miguel (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)

Data:	2024
Resum:	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.
Ajuts:	Agencia Estatal de Investigación PID2021-125258OB-I00 Agència de Gestió d'Ajuts Universitaris i de Recerca 2021/SGR-00643
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Publications of the Astronomical Society of the Pacific, Vol. 136, Issue 11 (November 2024) , art. 114506, ISSN 1538-3873

DOI: 10.1088/1538-3873/ad8b69

11 p, 1.4 MB

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