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  • Self-describing file format for gigapixel images?

    - by Adam Goode
    In medical imaging, there appears to be two ways of storing huge gigapixel images: Use lots of JPEG images (either packed into files or individually) and cook up some bizarre index format to describe what goes where. Tack on some metadata in some other format. Use TIFF's tile and multi-image support to cleanly store the images as a single file, and provide downsampled versions for zooming speed. Then abuse various TIFF tags to store metadata in non-standard ways. Also, store tiles with overlapping boundaries that must be individually translated later. In both cases, the reader must understand the format well enough to understand how to draw things and read the metadata. Is there a better way to store these images? Is TIFF (or BigTIFF) still the right format for this? Does XMP solve the problem of metadata? The main issues are: Storing images in a way that allows for rapid random access (tiling) Storing downsampled images for rapid zooming (pyramid) Handling cases where tiles are overlapping or sparse (scanners often work by moving a camera over a slide in 2D and capturing only where there is something to image) Storing important metadata, including associated images like a slide's label and thumbnail Support for lossy storage What kind of (hopefully non-proprietary) formats do people use to store large aerial photographs or maps? These images have similar properties.

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  • 9 Gigapixel Photo Captures 84 Million Stars

    - by Jason Fitzpatrick
    The European Southern Observatory has released an absolutely enormous picture of the center of the Milky Way captured by their VISTA telescope–the image is 9 gigapixels and captures over 84 million stars. From the press release: The large mirror, wide field of view and very sensitive infrared detectors of ESO’s 4.1-metre Visible and Infrared Survey Telescope for Astronomy (VISTA) make it by far the best tool for this job. The team of astronomers is using data from the VISTA Variables in the Via Lactea programme (VVV), one of six public surveys carried out with VISTA. The data have been used to create a monumental 108 200 by 81 500 pixel colour image containing nearly nine billion pixels. This is one of the biggest astronomical images ever produced. The team has now used these data to compile the largest catalogue of the central concentration of stars in the Milky Way ever created. Want to check out all 9 billion glorious pixels in their uncompressed state? Be prepared to wait a bit, the uncompressed image is available for download but it weighs in at a massive 24.6GB. 84 Million Stars and Counting [via Wired] How Hackers Can Disguise Malicious Programs With Fake File Extensions Can Dust Actually Damage My Computer? What To Do If You Get a Virus on Your Computer

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  • Building a workstation computer for Image processing? [closed]

    - by echolab
    I am taking a gigapixel image my goal is 50gigapixel and shooting is almost done , i am doing some research to build a workstation so i can stitch images together , my questions is ! Could u suggest some dual cpu mainboard that works fine with xeon 5500+ , with 64GB+ ram support ? My other question is which hardware is most important in image processing , all i see in story of gigapixel panoramas is they have dual xeon and 32gb+ ram ? i wonder if i am doing this right , i mean they don't post information on graphic card , mainboard and stuff ! I did asked several websites , but nothing best answer was get some high-end workstation and plenty of hours , i don't want to purchase ready to use workstations, i wanna build it up Thanks in advance

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