Image Mosaics

Tato bakalářská práce se zabývá vytvářením obrazových mozaiek - obrázků které jsou složeny z menších obrázků tak, aby se z dostatečné vzdálenosti jevily jako jeden celek. Dále se tato práce zabývá tvorbou databáze obrázků potřebných k vytváření mozaiek.This bachelor's thesis deals with creating picture mosaics - pictures, which are compound of a smaller pictures, so that they appears as integral units from the suffcient distance. This thesis also deals with generation of pictures database necessary to compositing mosaics.

Spitzer data at the NASA/IPAC Infrared Science Archive (IRSA)

The NASA/IPAC Infrared Science Archive (IRSA) curates and serves science data sets from NASA’s infrared and submillimeter projects and missions, including IRAS, 2MASS, MSX, SWAS, ISO, IRTS and from the Spitzer Space Telescope. All Spitzer data can be accessed from IRSA’s Spitzer mission page at: http://irsa.ipac.caltech.edu/Missions/spitzer.html Spitzer Legacy Enhanced Products along with ancillary data are delivered in six month intervals starting from Fall 2004, until Fall 2006. IRSA continually ingests the Spitzer data and the ancillary data, and these data are made accessible through IRSA’s query engines. Legacy products for the C2D, FEPS, GLIMPSE, GOODS, SINGS and SWIRE projects are accessible through a common interface http://irsa.ipac.caltech.edu/applications/Atlas. This engine returns the spatial footprints of observations and provides access to all flavors of released data sets, including, where appropriate, previews of image mosaics, 3-color image mosaics and spectra

The Montage Image Mosaic Service: Custom Image Mosaics On-Demand

The Montage software suite has proven extremely useful as a general engine for reprojecting, background matching, and mosaicking astronomical image data from a wide variety of sources. The processing algorithms support all common World Coordinate System (WCS) projections and have been shown to be both astrometrically accurate and flux conserving. The background ‘matching’ algorithm does not remove background flux but rather finds the best compromise background based on all the input and matches the individual images to that. The Infrared Science Archive (IRSA), part of the Infrared Processing and Analysis Center (IPAC) at Caltech, has now wrapped the Montage software as a CGI service and provided a compute and request management infrastructure capable of producing approximately 2 TBytes / day of image mosaic output (e.g. from 2MASS and SDSS data). Besides the basic Montage engine, this service makes use of a 16-node LINUX cluster (dual processor, dual core) and the ROME request management software developed by the National Virtual Observatory (NVO). ROME uses EJB/database technology to manage user requests, queue processing and load balance between users, and managing job monitoring and user notification. The Montage service will be extended to process userdefined data collections, including private data uploads

A review of parallel computing for large-scale remote sensing image mosaicking

Interest in image mosaicking has been spurred by a wide variety of research and management needs. However, for large-scale applications, remote sensing image mosaicking usually requires significant computational capabilities. Several studies have attempted to apply parallel computing to improve image mosaicking algorithms and to speed up calculation process. The state of the art of this field has not yet been summarized, which is, however, essential for a better understanding and for further research of image mosaicking parallelism on a large scale. This paper provides a perspective on the current state of image mosaicking parallelization for large scale applications. We firstly introduce the motivation of image mosaicking parallel for large scale application, and analyze the difficulty and problem of parallel image mosaicking at large scale such as scheduling with huge number of dependent tasks, programming with multiple-step procedure, dealing with frequent I/O operation. Then we summarize the existing studies of parallel computing in image mosaicking for large scale applications with respect to problem decomposition and parallel strategy, parallel architecture, task schedule strategy and implementation of image mosaicking parallelization. Finally, the key problems and future potential research directions for image mosaicking are addressed

A Cost-Benefit Study of Doing Astrophysics On The Cloud: Production of Image Mosaics

Utility grids such as the Amazon EC2 and Amazon S3 clouds offer computational and storage resources that can be used on-demand for a fee by compute- and data-intensive applications. The cost of running an application on such a cloud depends on the compute, storage and communication resources it will provision and consume. Different execution plans of the same application may result in significantly different costs. We studied via simulation the cost performance trade-offs of different execution and resource provisioning plans by creating, under the Amazon cloud fee structure, mosaics with the Montage image mosaic engine, a widely used data- and compute-intensive application. Specifically, we studied the cost of building mosaics of 2MASS data that have sizes of 1, 2 and 4 square degrees, and a 2MASS all-sky mosaic. These are examples of mosaics commonly generated by astronomers. We also study these trade-offs in the context of the storage and communication fees of Amazon S3 when used for long-term application data archiving. Our results show that by provisioning the right amount of storage and compute resources cost can be significantly reduced with no significant impact on application performance