Fusion
The Fusion operation  allow combination of images with different spectral and spatial resolution keeping the radiometric information. Huge effort has been put in developing fusion methods that preserve the spectral information and increase detail information in the hybrid product produced by fusion process. The available methods in TerraLib are:
  • IHS: Fusion of a low-resolution multi-band image with a high resolution image using the IHS method. The IHS method consists on transforming the R,G and B bands of the multispectral image into IHS components, replacing the intensity component by the panchromatic image, and performing the inverse transformation to obtain a high spatial resolution multispectral image.
  • PCA:  Fusion of a low-resolution multi-band image with a high resolution image using the PCA (Principal components analysis) method. The PCA performs image fusion where the first principal component of the multi-spectral image is replaced by the histogram matched panchromatic imagery.
  • WISPER:  Fusion of a low-resolution multi-band image with a high resolution image using the WiSpeR method.
It is accessible through:
   Raster Processing > Fusion... (list of all raster layers will be available) 

This wizard consists of the following steps:

   Wizard Page 1 - Selection of the raster layer with a LOWER resolution (Layer Search)

  1. On the List of Layers select the raster layer with a lower resolution. Optionally use Filter By Name  field giving part of the layer name to help find the layer in the list.
  2. Press Next  to go to next step or Cancel to close the dialog. 

   Wizard Page 2 - Selection of the raster layer with a HIGHER resolution (Layer Search)

  1. On the List of Layers select the raster layer with a higher resolution. Optionally use Filter By Name  field giving part of the layer name to help find the layer in the list.
  2. Press Next  to go to next step or Cancel to close the dialog.

    Wizard Page 3 - Fusion parameters

  1. Select the Type of fusion to be used and set the their specific parameters. 
    • IHS
      • Select the raster band index to process from the high resolution raster..
      • Select the raster band index from the lower resolution raster  for  the red channel.
      • Select the raster band index from the lower resolution raster  for  the green channel.
      • Select the raster band index from the lower resolution raster  for  the blue channel.
    • PCA
      • Select the raster band index to process from the high resolution raster..
      • Select each raster band index from the lower resolution raster  will be part of the process.
      • Select the high resolution image histogram fitting method:
        • No fitting
        • Mean and Standard deviation fitting
        • Minimum and maximum value fitting
        • Fitting by using mean and Standard deviation and clipping to minimum and maximum values
    • WISPER
      • Select the raster band index to process from the high resolution raster.
      • Set the sensor type for the selected band.
      • Select and set the sensor type to each band of the lower resolution raster.
      • Select the filter type (wavelet parameter).
      • Define the number of decomposition levels  (wavelet parameter).
  2. The common options for all methods is:
    • Select the interpolator method to be used.
    • Select the output raster no-data value or leave blank to use the same as the input low-resolution raster no-data value.
    •  Crop rasters to overlap area. This is necessary if the input rasters has different extents.
  3. Press Next to apply the contrast or Back to go to the previous wizard page.

    Wizard Page 4 - Output information

  1. Raster Info - First press and inform the folder where the resulting file will be saved.
  2. Name - inform the raster name.
  3. Extra Parameters - if there are some, see the details on how to inform then here.
  4. Press Finish to save the resulting contrasted raster or Back to go to the previous wizard page.
Hint: The resulting image will be added as a new layer at the TerraView project.