April 2013
Intermediate to advanced
1164 pages
39h 37m
English
Content preview from Hyperspectral Data Processing: Algorithm Design and AnalysisBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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6.3 Dimensionality Reduction by High-Order Statistics-Based Components Analysis Transforms
Recall that 
is the set of image pixel vectors in a hyperspectral image where 
is a data matrix that represents an image cube as an L × N data matrix formed by 
with 
. Let w be an L-dimensional column vector and assumed to be a desired projection vector. Then 
is an 
column vector that represents the projection of the entire hyperspectral image pixel vectors 
being mapped along the direction of w. Now, assume that 
is a function to be explored and defined on the projection space 
. The selection of the function ...
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