| The customer's ability to render a judgement of
the quality of an image is based on the recognition that when we
observe an image we have certain well established psychological
expectations. |
Sharpness
The ability to render fine detail is seen as sharpness. Your
customer expects that fine detail such as the model's hair is
crisply reproduced. Image Integration offers tools to measure,
analyze and quantify sharpness dependent image quality. |
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Memory Colors
 The viewer remembers colors such as skin tones, blue sky and
foliage and expects them to be rendered accurately. Image Integration offers tools to measure, model and manage the
reproduction of the full palette of colors. |
Noise
The customer expects to see areas such as skin free of
granularity and uniformity defects. Granularity may arise from
dot microstructure; hardware components of printers and imagers
may introduce uniformity defects such as banding or streaks.
Image Integration offers tools to measure, analyze and quantify
noise dependent image quality. |
Tone Scale
 The viewer expects not only a proper lightness rendition of the
image, but also the rendition of detail in both the shadows and
highlights. Image Integration offers tools to measure and manage
the optimal rendition of image brightness. |
 Customer Image Quality
The degree to which these expectations are met will determine
the perceived image quality. Image Integration offers
tools and
protocols for the direct measurement of your customer's
assessment of image quality. |
