principal_comp — Compute the principal components of multichannel images.
principal_comp(MultichannelImage : PCAImage : : InfoPerComp)
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.
Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.
MultichannelImage (input_object) (multichannel-)image → object (byte* / direction* / cyclic* / int1* / int2* / uint2* / int4* / real*) *allowed for compute devices
Multichannel input image.
PCAImage (output_object) multichannel-image → object (real)
Multichannel output image.
InfoPerComp (output_control) real-array → (real)
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.
Foundation