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If d T X is small, the difference between the pixel vector X and the target vector d is large.
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So, we put all the pixel vectors into a column, and select a pixel vector after several pixels apart to form a sample set.
It should be noted that the SAD between a pixel vector selected by the PPI and a reference spectral signature is given by (4).
For characterizing each pixel in the transducer, we study the statistics of associated pixel vector: the collection of all density measurements from that pixel throughput the dataset10.
After the a posteriori data normalization, all pixel vectors will show the same statistical behaviour in that each pixel vector will have the same average density and the same standard deviation.
Associated with each pixel vector, the corresponding image coordinates were saved for a later reconstruction of the compositional images.
First, the window pixel vectors are almost never statistically independent.
The thus corrected images are normalized to zero mean and unit standard deviation per pixel vector throughout the dataset.
(1) First, a pixel purity score is calculated for each pixel vector in the input hyperspectral image cube by generating random, -dimensional vectors, called skewers.
We characterize each pixel in terms of the average density and standard deviation of its pixel vector and exploit that information to normalize its output.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com