Perceptual quality based automatic parameter selection for data compression
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United States of America Patent
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Issued Date -
Aug 16, 2007
app pub date -
Feb 13, 2006
filing date -
Feb 13, 2006
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Abandoned
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Abstract
The automatic and optimal selection of coding parameter values according to analyses of coding trials is disclosed. The Neural Encoding Model (NEM) provides a method for providing a quantitative measure of the likelihood that a human observer can distinguish an original sensory signal from an approximation thereof, thus providing a metric by which the effect of various coding parameters may be analyzed and optimized. Optimal coding parameters can be defined for an entire data set, such as a digitized audio file, or for discrete portions of the data set. A trial coded data set or portion thereof is analyzed to determining if certain coding parameters have been assigned optimal values. If not, parameter manipulation is performed in an intelligent order and the objective analysis is repeated until predetermined objective perceptual distance criteria are achieved.
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