pca
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(Difference between revisions)
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Principal Component Analysis | Principal Component Analysis | ||
| − | Compute the principal components of | + | Compute the principal components of an N band real data image |
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| + | NOTE: for the old 3 band pca version see [[pca_byte|pca_byte()]]. This version replaced the old byte version on 2-9-2011 | ||
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Arguments: A numeric array and ignore value | Arguments: A numeric array and ignore value | ||
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Return Value: The rotated data | Return Value: The rotated data | ||
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| − | [[Syntax]]: pca(image) | + | [[Syntax]]: pca(image [, ignore=FLOAT][, struct=BOOL]) |
| − | 'image' - A | + | 'image' - A N-band image or data array |
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| + | 'ignore' - the ignore value for the black space of an image | ||
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| + | 'struct' - return the eigen vectors/values and covariance matrix | ||
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dv> a | dv> a | ||
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*[[pca2]] | *[[pca2]] | ||
| + | *[[pca_byte]] | ||
| + | *[[eigen2]] | ||
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*general_science.dvrc | *general_science.dvrc | ||
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| + | 1.02 | ||
}} | }} | ||
[[category:Functions]] | [[category:Functions]] | ||
[[category:User Defined Functions]] | [[category:User Defined Functions]] | ||
[[category:Matrix]] | [[category:Matrix]] | ||
Revision as of 13:23, 9 February 2011
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Contents: Description, Arguments, Usage, Examples, Images, Sub-Functions, Related Functions, Source Supported Under Version: >1.00
Description Principal Component Analysis Compute the principal components of an N band real data image NOTE: for the old 3 band pca version see pca_byte(). This version replaced the old byte version on 2-9-2011
Arguments and Return Values Arguments: A numeric array and ignore value Return Value: The rotated data
Usage dv> a 600x600x3 array of byte, bip format [1,080,000 bytes] dv> b=pca(a) data: 600x600x3 array of double, bip format [8,640,000 bytes]
Examples Original Image
Three principal components
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Recent Library Changes Created On: 02-15-2006 |
