Primary features of i2e
Adaptive Brightness and
Contrast Enhancement (ABE). ABE uses object recognition
technology to classify images and determine optimal settings
for white point, black point, and gamma correction. This enhancement
process is applied to the whole image.
Shadow and Highlight Enhancement
(SHE). SHE enhances detail in shadow and highlight
areas. For example, flash portraits taken at night can have
extreme shadows and highlights. SHE enhances the details in
these trouble areas to reduce contrast and improve object
visibility.
Memory Color Enhancement
(MCE). MCE is a local color enhancement for key colors.
Key colors, such as skin color, vegetation, and the sky have
an associated reference color that MCE has memorized. For
example, vegetation should show a nice saturated green and
should lack blue; the sky should be more blue than gray.
Local Sharpeness Enhancement
(LSE). LSE performs a variable sharpening of the image
depending on object recognition algorithms. Use LSE to sharpen
vegetation and edges, and to smooth objects like sky or faces.
LSE works especially well with low resolution images, such
as images coming from camera equipped cell phones.
Local Noise Reduction (LNR).
LNR performs a special noise reduction on parts of the image,
primarily thermal noise in the spatial domain. As a filter,
it is especially useful to eliminate noise that could reduce
the effectiveness of a shadow enhancement. LNR can also reduce
quanitization noise due to high compression. LNR exceeds the
capabilities of a standard noise reduction filter because
it preserves edges and acts on the areas of the image that
need it. Blanket noise reduction filters frequently make an
entire image unsharp.
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