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SeDDaRA Image Gallery
Home Pictures
Sometimes
the perfect 'shot' turns out to be not so perfect. This can result
from an imperfect camera, imperfect conditions, or perhaps an imperfect
camera person. Either way,
blind deconvolution may be able restore the image to its intended
clarity.
And our technique is easy to apply and master, so give Tria Image Processing a try.
The group shot that you would have
liked to be in focus.
Run your mouse over the
image to reveal the restored figure.
Caution: Applying
deconvolution methods to images captured on consumer-grade digital
cameras is hit-or-miss. JPEG compression greatly reduces the
chances for total restoration. In addition, the bit depth also
truncates information about the blur function. We recommend that
you always save your images at the highest quality setting, and check
your camera viewer at the highest magnification to check the
quality.
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Fig1: An RGB Image of
the U.S.S. Constitution, taken intentionally out-of-focus with a
digital camera, in Baltimore's Inner Harbor.
Run your mouse over the
image to reveal the restored figure.
Fig 2: The image was separated into its three colors (Red, Green, and
Blue). Each component was restored, and the image was put back
together.
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Fig1: An RGB Image,
taken
intentionally out-of-focus with a digital camera, of a parking
lot in Baltimore.
Run your mouse over the
image to reveal the restored figure.
Fig 2: The image was separated into its three colors (Red,
Green, and Blue). Each component was restored, and the image
was put back together.
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The above images were taken by
Yuqiao Yang, Newark DE, to demonstrate the technique.
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Fig1: This image was
scanned from a projection slide taken in 1959.
Run your mouse over the
image to reveal the restored figure.
Fig 2: The SeDDaRA algorithm was used to remove the blur.
However, dust particles on the slide created some artifacts.
Photoshop was used to de-emphasize the dust particles and balance the
colors.
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