Kneson Progressive Photo Enlargement Method |
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| The Kneson Progressive
photo enlargement method analyzes pixels beyond the immediate
pixels of each dot in the image. This photo enlargement method
is found in Kneson Software's
Imagener Enhanced
version. This interpolation method intelligently weighs
the difference of colors in outlying pixels far beyond those
analyzed by Bicubic analysis. This difference, weighed with
the distance to each point or dot in the image, is used to
enlarge images with a much more satisfactory result than
Bicubic interpolation method produces. |
Kneson Progressive++ Photo Enlargement Method |
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| The Kneson Progressive++
photo enlargement method improves on the Kneson Progressive
photo enhancement method by leveraging the power of the programming
language C++ for pixel information analysis. This method
analyzes information for each dot, then performs a second
analysis of each pixel in the array of pixels used in the
original analysis. This image enlargement method is found
in Kneson Software's Imagener Professional
version and is more sensitive and complete in its enlargement
decision matrix, resulting in sharper edges and more careful
blending to image areas containing gradient color changes. |
Kneson Unlimited Photo Enlargement Method |
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| The Kneson Unlimited
photo enlargement method is the world's first pixel-to-vector
enlargement technology, and is found in Kneson
Software's Imagener Unlimited
version. This enlargement method is a revolutionary departure
in enlargement algorithm logic. It does not work with pixels
-- it analyzes an image for regions that make up similar
color groups at an invisible-to-the-eye detail level. The
initial analysis stage creates detailed regions down to the
single-pixel level. This enlargement method then analyzes
the image complexity, and assigns complexity values to each
region, using these values to compute a finely tuned vector
array throughout the entire image. The Kneson Unlimited enlargement
method then converts these pixel groups into vectors defining
regions that make up the content of the image. This process
alone vastly improves the look of all images even before
enlargement. Once the image has been encoded into regions
(vectors), even the most complex images can be resized without
limit as the region can be resized like a rubber band. The
resulting image has outstanding clarity even at massive proportions. |
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