pca
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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 |
+ | |||
+ | 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 |
+ | |||
+ | 'ignore' - the ignore value for the black space of an image | ||
+ | |||
+ | 'struct' - return the eigen vectors/values and covariance matrix | ||
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dv> a | dv> a | ||
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data: 600x600x3 array of double, bip format [8,640,000 bytes] | data: 600x600x3 array of double, bip format [8,640,000 bytes] | ||
| | | | ||
− | Original Image | + | Original 3-band Image: |
[[Image:unfiltered.png|250px]] | [[Image:unfiltered.png|250px]] | ||
− | Three principal components | + | Three principal components: |
[[Image:comp1.png|250px]] [[Image:comp2.png|250px]] [[Image:comp3.png|250px]] | [[Image:comp1.png|250px]] [[Image:comp2.png|250px]] [[Image:comp3.png|250px]] | ||
+ | |||
+ | Original 6-band Image: | ||
+ | |||
+ | [[Image:NYC-Band_Comparison.PNG|300px]] | ||
+ | |||
+ | Six principal components: | ||
+ | |||
+ | [[Image:NYC-PCA-C1.PNG|300px]] [[Image:NYC-PCA-C2.PNG|300px]] [[Image:NYC-PCA-C3.PNG|300px]] [[Image:NYC-PCA-C4.PNG|300px]] [[Image:NYC-PCA-C5.PNG|300px]] [[Image:NYC-PCA-C6.PNG|300px]] | ||
+ | |||
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*[[mxm]] | *[[mxm]] | ||
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*[[covar]] | *[[covar]] | ||
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+ | *[[eigen2]] | ||
+ | *[[kt1]] | ||
+ | *[[kt2]] | ||
+ | *[[kt3]] | ||
+ | *[[kt4]] | ||
+ | *[[kt5]] | ||
+ | *[[kt6]] | ||
*[[pca2]] | *[[pca2]] | ||
+ | *[[pca_byte]] | ||
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− | + | *general_science.dvrc | |
| | | | ||
+ | 1.02 | ||
}} | }} | ||
[[category:Functions]] | [[category:Functions]] | ||
[[category:User Defined Functions]] | [[category:User Defined Functions]] | ||
[[category:Matrix]] | [[category:Matrix]] |
Latest revision as of 17:36, 15 July 2012
Contents: Description, Arguments, Usage, Examples, Images, Sub-Functions, Related Functions, Source Supported Under Version: > 1.02
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 Syntax: pca(image [, ignore=FLOAT][, struct=BOOL]) 'image' - A N-band image or data array 'ignore' - the ignore value for the black space of an image 'struct' - return the eigen vectors/values and covariance matrix
Examples 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]
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Recent Library Changes Created On: 02-15-2006 |