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Maximum noise fraction.
Optimized maximum noise fraction transformation.
One of the most popular ones is the maximum noise fraction (MNF) transform [6, 7].
Then, an optimized maximum noise fraction (OMNF) transform is proposed for dimensionality reduction of HJ-1A images, which adopts an accurately estimated noise covariance matrix for noise whitening.
Specifically we have used a Maximum Noise Fraction (MNF) [29] transformation to remove the image background material (petri dish and cardboard under the petri dish).
Several methods for determining the number of end-member are reported in the literature, ranging from relatively simple techniques like principal component and independent component analysis to more complicated techniques like virtual dimensionality [ 32], maximum noise fraction [ 33] and noise adjusted principal components [ 34] and many more.
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Finally, the spectral images are processed in ENVI+IDL (ITT Visual Information Solutions, Boulder, CO, USA) using a minimum noise fraction (MNF) algorithm that removes the noise dominated principal components.
On subway platforms, the mean maximum noise level was 94 decibels.
where ε2is the maximum noise power.
Maximum noise levels vary from 91.9 dB to 100.7 dB.
In this paper, we analyzed the measured maximum noise levels.
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