Principal Component Analysis

Calculate the eigenvalue, covariance, correlation coefficient and positive selection of each data.

Click Spectrum > Principal Component Analysis.

Click the Spectrum Subset button to select the band of the hyperspectral image.

Input hyperspectral image data: Input the hyperspectral image data file. Data should be pre-processed, such as radiation calibration and atmospheric correction.
Band selection: Select the band of the hyperspectral image. For PCA function, please click Clear the bad band before using it.
Resampling rate X: Used to set the ratio of resampling. The smaller the value, the fewer the number of cells involved in the calculation, the faster the calculation speed, the range is 0-1.
Resampling rate Y: Used to set the ratio of resampling. The smaller the value, the fewer the number of cells involved in the calculation, the faster the calculation speed, the range is 0-1.
Calculation method: Covariance matrix: suitable for situations where data differences between bands are small. Correlation coefficient matrix: suitable for situations where data differences between bands are large.
Resampling Method: Specifies the resampling technique that will be used to build the pyramids.
Threshold Value: The processing threshold (default value is 5000) is used to adjust the analysis precision. A higher value results in greater precision but slower processing speed.
ROI: Only the minimum external rectangle in the ROI area is calculated after selection.
Mask: Only the effective area of the mask is calculated after selection.
Output MNF file: Output MNF statistics.
Output path: The generated tif path.

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