principal_comp — Compute the principal components of multichannel images.
principal_comp does a principal components analysis of multichannel images. This is useful for images obtained, e.g., with the thematic mapper of the Landsat satellite. Because the spectral bands are highly correlated, it is desirable to transform them to uncorrelated images. This can be used to save storage, since the bands containing little information can be discarded, and with respect to a later classification step.
The operator principal_comp takes a (multichannel) image MultichannelImage and transforms it to the output image PCAImage, which contains the same number of channels, using the principal components analysis. The parameter InfoPerComp contains the relative information content of each output channel.
principal_comp can be executed on OpenCL devices if image consists of eight channels or less. Since the calculations are done in single precision floating point, the results may differ from those calculated by the CPU.
Multichannel input image.
Multichannel output image.
Information content of each output channel.
The operator principal_comp returns the value 2 (H_MSG_TRUE) if the parameters are correct. Otherwise an exception is raised.