Gallery 5 Consumer
  • Original RGB Image of a mountain at dusk in the Southwest United States.  The image contains a flat blue sky and a red mountain with signifcant 'high-spatial'  features.
  •   The image was seperated into its three colors (Red, Green, and Blue).  Each component was restored, and the image was put back together. Note the improved resolution in the mountain and no artifacting occuring at the mountain sky boundary.
  • This image was scanned from a projection slide taken in 1959.
  • 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.
  • An RGB Image of the USS Constellation, taken intentionally out-of-focus with a digital camera, in Baltimore's Inner Harbor.
  • The image was separated into its three colors (Red, Green, and Blue).  Each component was restored, and the image was put back together.
  • This image was originally taken with a Brownie camera a long time ago.
  • Restored Image. The process removes any of the original blur that can possibly be pulled out of the digital image.
  • A group shot taken with shaky hands.
  • The restoration.
  • An RGB Image, taken intentionally out-of-focus with a digital camera,  of a parking lot in Baltimore.
  • The image was separated into its three colors (Red, Green, and Blue). Each component was restored, and the image was put back together.
  • The group shot that you would have liked to be in focus.
  • Restored Image.
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Consumer Images

 

It may be surprising to know that at a time where just about everyone has a camera attached to their smartphone, that consumer images are not a prime part of our business.  The main reason is that there are so many pictures being taken, that cleaning up blurry ones is not a priority.  The exception is when you take that one shot that cannot be captured again.  The slideshow above has some examples of these.

 

This image, dating from the 1950's was scanned in from a slide.  The blind deconvolution was able to identify the blur and remove much of it.  Some of the artifacts were produced by scratches and dust on the slide.  We adjusted the colors afterward to give the image a more realistic view.

 

 

This is a rather uninteresting image of a parking lot in Balitmore, Maryland, taken by a friend of mine.  Noticing the blur, I asked if I could see what SeDDaRA could restore.  There is a little artifacting around bright objects, as a result of the jpeg compression, but the resolution is greatly improved.

 

 

This image is quite interesting, both for its content and for the clean-up.  The image was scanned from a photograph taken with a Brownie camera, a low-cost Kodak camera.  The women are hanging an outhouse for unknown reasons.  The constrast that came out of the image is incredible.

 

 

Getting this many people together for a picture is a feat in iteslf.  Unfortunately, the person at the controls may not have the steadiest hands.  This image proved difficult to fully restore since the people are darker than the surroundings.  This means that the 'signal' of that portion of the image is close to the 'noise'.  Much of the content of the blur is therefore lost in the noise.  Nonetheless, the deconovlution produced a modest improvement.

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Quarktet Diamond