2009/06/08 by Daniel Mueller, George Dimitoglou, Mueller, Daniel +22 · 5 citations
Computer Science · Physics and Astronomy · #Advanced Data Compression Techniques #Big data #Computer science #Computer vision #Data mining #Data science #FOS: Physical sciences #Image (mathematics) #Image Retrieval and Classification Techniques #Image and Signal Denoising Methods #Instrumentation and Methods for Astrophysics (astro-ph.IM) #JPEG #Metadata #Operating system #Petabyte #Software #Solar and Stellar Astrophysics (astro-ph.SR) #Terabyte #Visualization #World Wide Web #astro-ph.IM #astro-ph.SR
paper · pdf · doi:10.48550/arxiv.0906.1582
published in arXiv (Cornell University) (Cornell University) · 19 pages, 7 figures, accepted for publication in Computing in Science and Engineering
arxiv created 2009/06/08 · openalex publication_date 2009/06/08 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Across all disciplines that work with image data - from astrophysics to medical research and historic preservation - there is a growing need for efficient ways to browse and inspect large sets of high-resolution images. We present the development of a visualization software for solar physics data based on the JPEG 2000 image compression standard. Our implementation consists of the JHelioviewer client application that enables users to browse petabyte-scale image archives and the JHelioviewer server, which integrates a JPIP server, metadata catalog and an event server. JPEG 2000 offers many useful new features and has the potential to revolutionize the way high-resolution image data are disseminated and analyzed. This is especially relevant for solar physics, a research field in which upcoming space missions will provide more than a terabyte of image data per day. Providing efficient access to such large data volumes at both high spatial and high time resolution is of paramount importance to support scientific discovery.