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arXiv 1702.01946astro-ph.SR
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太阳EUV图像的JPEG2000图像压缩

JPEG2000 Image Compression on Solar EUV Images

C. E. Fischer, D. Müller, I. De Moortel

摘要:

对于未来的太阳能任务以及地面望远镜,返回和处理数据的有效方法变得越来越重要。太阳轨道器,例如,这是欧空局/美国航天局探索太阳和日光层的下一个任务,是一项深空任务,这意味着有限的遥测速率,使得有效的机载数据压缩成为实现任务科学目标的必要条件。像太阳动力学天文台(SDO)和未来的地面望远镜,如丹尼尔K。另一方面,Inouye太阳望远镜面临的挑战是使太阳能社区能够访问拍字节大小的太阳数据档案。新的图像压缩标准通过实施可根据用户要求定制的高效灵活的压缩算法来解决这些挑战。我们分析太阳图像从大气成像组件(AIA)的仪器机载SDO研究有损JPEG 2000(从联合摄影专家组2000年)图像压缩在不同的比特率的效果。为了评估压缩图像的质量,我们使用平均结构相似性(MSSIM)指数以及广泛使用的峰值信噪比(PSNR)作为度量标准,并在太阳EUV图像的背景下比较两者。此外,我们进行测试,以验证科学使用的有损压缩图像分析的例子,在磁盘和离肢体冠状动脉环振荡时间序列观察AIA/SDO。

英文摘要:

For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, e.g., which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bit rates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disk and off-limb coronal-loop oscillation time-series observed by AIA/SDO.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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