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Identifying regions of interest (ROIs) in images is a very active research problem as it highly depends on the types and characteristics of images. In this paper we present a comparative evaluation of unsupervised learning methods, in particular clustering, to identify ROIs in solar images from the Solar Dynamics Observatory (SDO) mission. With the purpose of finding regions within the solar images...
In this work we present an alternative approach for large-scale retrieval of solar images using the highly-scalable retrieval engine Lucene. While Lucene is widely popular among text- based search engines, significant adjustments need to be made to take advantage of its fast indexing mechanism and highly-scalable architecture to enable search on image repositories. In this work we describe a novel...
In this work, we discuss the benefits of image compression on FITS image files to perform image retrieval tasks on the enormous NASA Solar Dynamics Observatory (SDO) image repository. With the objective of making solar image files more portable and easy to distribute and archive, we test several lossless compression algorithms as well as lossy compression algorithms in order to determine the rate...
In this work we present a composite method for image parameter evaluation using Scale-Invariant Feature Transform (SIFT) descriptors and bag of words representation applied to pre-selected image parameters, with potential applications to solar data and other domains. As one of the main challenges in computer vision, image parameter evaluation has been approached from supervised and unsupervised perspectives...
In this work we present our first results on the ambitious task of providing region-based querying capabilities to our existing Solar Dynamics Observatory (SDO) content-based image-retrieval (CBIR) system. By taking advantage of precomputed image descriptors, we calculate region-based histogram signatures for our training set of previously identified solar events. With these signatures we then explore...
In this work we report on the transfer of image parameters that produce good results for medical images to the domain of solar image analysis. Using the first solar domain-specific benchmark dataset that contains multiple types of solar phenomena we discovered during our work for constructing a content-based image retrieval (CBIR) system for NASA's Solar Dynamics Observatory (SDO) mission that we...
This work describes the attribute evaluation sections of the ambitious goal of creating a large-scale content-based image retrieval (CBIR) system for solar phenomena in NASA images from the Solar Dynamics Observatory mission. This mission, with its Atmospheric Imaging Assembly (AIA), is generating eight 4096 pixels × 4096 pixels images every 10 seconds, leading to a data transmission rate of approximately...
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