principal_comp — 计算多通道图像的主成分。
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.
算子 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.
请注意，若使用域缩减后的图像作为输入，滤波器算子可能会返回意外结果。请参阅 滤波器 一章
MultichannelImage (输入对象) (multichannel-)image → object (byte* / direction* / cyclic* / int1* / int2* / uint2* / int4* / real*) *允许用于计算设备
Multichannel input image.
PCAImage (输出对象) multichannel-image → object (real)
Multichannel output image.
InfoPerComp (输出控制) real-array → (real)
Information content of each output channel.
算子 principal_comp 在参数正确时返回值 2 ( H_MSG_TRUE )。否则将抛出异常。
基础