pca2
Contents: Description, Arguments, Usage, Examples, Images, Sub-Functions, Source Supported Under Version: >1.00
Description This function computes principal component images from an input image and a set of eigenvectors. This function is different from pca in that it allows for application to various multiband images in multibple data formats. It also take the output from eigen2, which calculates the eigenvectors the slow way, which greatly increases the accuracy of higher order eigenvectors and eigenvalues.
Arguments and Return Values Arguments: Input image cube, output structure from eigen2. Return Value: Image cube with the same x and y dimensions as the input and the same z dimension as the number of input eigenvectors and aigenvalues.
Usage Syntax: jpca(image,ev) image: surface pressure (m x n x k array) ev: output structure from eigen2 containing .evecs (k x j x 1 array), .evals (j x 1 x 1 array), .avg (k x 1 x 1 array), and .C (i x j x 1 array) Arrays are arbitrary in size, but 'k' must be the same in image and ev.evecs.
Examples
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Recent Library Changes Created On: 01-01-2008 |