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PC Spectral Sharpening

PC Spectral Sharpening

Use PC Spectral Sharpening to sharpen a low spatial resolution multi-band image using an associated high spatial resolution panchromatic band. The algorithm assumes that the low spatial resolution spectral bands correspond to the high spatial resolution panchromatic band. If both data sets are georeferenced, ENVI additionally co-registers them on the fly.

You can also write a script to perform PC spectral sharpening using the ENVIPCPanSharpeningTask routine.

See the following sections:

Background


ENVI applies Principal Components (PC) spectral sharpening by:

  1. Performing a PC transformation on the multispectral data.
  2. Replacing PC band 1 with the high resolution band and scaling the high resolution band to match the PC band 1, so no distortion of the spectral information occurs. The PC spectral sharpening method assumes that the first PC band is a good estimate of the panchromatic data.
  3. Performing an inverse transform.
  4. Resampling the multispectral data to the high resolution pixel size using a nearest neighbor, bilinear, or cubic convolution technique.

Run the PC Spectral Sharpening Tool


The images must be georeferenced or have the same image dimensions. If the images are georeferenced, ENVI co-register the images before performing the sharpening.

To apply PC spectral sharpening:

  1. From the Toolbox, select Image Sharpening > PC Spectral Sharpening. The Principal Components Pan Sharpening dialog appears.
  2. In the Input Low Resolution Raster field, select a low spatial resolution multispectral input file. Perform optional spatial and spectral subsetting, and/or masking, then click OK.
  3. In the Input High Resolution Raster field, select a high-resolution input image. Perform any optional spatial subsetting, then click OK.
  4. Select the resampling method from the Resampling drop-down list. The choices are:
    • Bilinear (default): Performs a linear interpolation using four pixels to resample
    • Nearest Neighbor: Uses the nearest pixel without any interpolation
    • Cubic Convolution: Uses 16 pixels to approximate the sinc function using cubic polynomials to resample the image.
  5. Enter a filename and location for the Output Raster.
  6. Enable the Preview check box to see a preview of the settings before you click OK to process the data. The preview is calculated only on the area in the Image window and uses the resolution level at which you are viewing the image. See Preview for details on the results.
  7. Enable the Display result check box to display the output image in the Image window when processing is complete.
  8. Click OK. ENVI adds the resulting output to the Data Manager and, if the Display Result check box was enabled, adds the layer to the Layer Manager and displays the output in the Image window.

References


Welch, R. and W. Ehlers. "Merging Multiresolution SPOT HRV and Landsat TM Data." Photogrammetric Engineering & Remote Sensing 53, No. 3 (1987): 301-303.

See Also


CN Spectral Sharpening, Gram-Schmidt Pan Sharpening, NNDiffuse Pan Sharpening,



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