See the following sections:

Apply Gain and Offset

Use Apply Gain and Offset to apply a simple gain and offset correction to a set of bands. ENVI multiplies the selected bands by an input gain value and adds an offset value that you define.

  1. From the Toolbox, select Radiometric Correction > Apply Gain and Offset. A Data Selection dialog appears.
  2. Select an input raster and perform optional spatial and spectral subsetting, then click OK. The Apply Gain and Offset dialog appears.
  3. Enter Gain Values for each band by selecting the band name and entering a value in the Edit field. If the input raster already contained gain metadata, those values are automatically populated in the Gain Values list. You can also restore gain values from an ASCII file by clicking the Import from ASCII file button and selecting a text file.
  4. Enter Offset Values for each band by selecting the band name and entering a value in the Edit field. If the input raster already contained offset metadata, those values are automatically populated in the Offset Values list. You can also restore offset values from an ASCII file by clicking the Import from ASCII file button and selecting a text file.

  5. To write the output to disk, select the File radio button and specify a filename and location. To produce output in memory only, select the Virtual radio button.

  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 view and uses the resolution level at which you are viewing the image. See Preview for details on the results. To preview a different area in your image, pan and zoom to the area of interest and re-enable the Preview option.
  7. Enable the Display result check box to display the output in the view when processing is complete. Otherwise, if the check box is disabled, the result can be loaded from the Data Manager.

  8. To reuse these task settings in future ENVI sessions, save them to a file. Click the down arrow and select Save Parameter Values, then specify the location and filename to save to. Note that some parameter types, such as rasters, vectors, and ROIs, will not be saved with the file. To apply the saved task settings, click the down arrow and select Restore Parameter Values, then select the file where you previously stored your settings.

  9. To run the process in the background, click the down arrow and select Run Task in the Background. If an ENVI Server has been set up on the network, the Run Task on remote ENVI Server name is also available. The ENVI Server Job Console will show the progress of the job and will provide a link to display the result when processing is complete. See ENVI Servers for more information.

  10. Click OK.

Cross-Track Illumination Correction

Use Cross-Track Illumination Correction to remove variation in the cross-track illumination of an image. Cross track illumination variations may be due to vignetting effects, instrument scanning, or other non-uniform illumination effects. Along-track mean values are calculated and you can plot them to show the mean variation in the cross-track direction. A polynomial function, with an order that you define, is fit to the means and used to remove the variation.

  1. From the Toolbox, select Radiometric Correction > Cross-Track Illumination Correction. The Input File dialog appears.
  2. Select an input file and perform optional spatial and spectral subsetting, and/or masking, then click OK. The Cross Track Illumination Correction Parameters dialog appears.
  3. Select the cross track direction by selecting the check box next to either Samples or Lines.
  4. Select either an Additive or Multiplicative correction method. The Additive method will subtract the fitted polynomial from the data and the Multiplicative method will divide the data by the fitted polynomial.
  5. Enter the polynomial order and click Plot Polynomial. A plot of the mean data values display in red with the selected polynomial fit overlaid in white. It is best to use a low order polynomial so as not to remove the local variation in the data.

    6. You can change the polynomial order and plot it again.

  6. Select output to File or Memory.
  7. Click OK.

Note: The Cross-Track Illumination Correction plot drop-down buttons are not active until you close the Cross Track Illumination Correction Parameters dialog.

EFFORT Polishing

Use Effort Polishing to run Empirical Flat Field Optimal Reflectance Transformation (EFFORT) to determine and apply mild adjustments to apparent reflectance data, so the spectra appear more like spectra of real materials.

Summary

Consistent noise or error features may appear in hyperspectral apparent reflectance data because of the limited accuracy of the standards, measurements, and models that were used and the limited accuracy of calibrations performed along the data signal processing chain. This cumulative error may be several percent in each spectral band, leading to apparent reflectance data with absolute accuracies far less than the actual precision of the original data.

EFFORT searches for a mild linear correction, bootstrapped from the data themselves, that polishes out this error and attempts to improve the accuracy of the apparent reflectance data. The EFFORT correction applies statistically mild adjustments to every band (gains near 1 and offsets near 0) that make a visual improvement in the apparent reflectance spectra. This removal of the cumulative errors of calibration and atmospheric correction allows improved comparison of EFFORT corrected spectra to library spectra.

The EFFORT process is similar to the Empirical Line method of data calibration, which matches data spectra to field-measured spectra. EFFORT, however, uses no ground truth data, and the EFFORT-calculated gains and offsets are applied to atmospherically corrected apparent reflectance data (for example, output from the ENVI Atmospheric Correction Module). EFFORT uses the data to generate "pseudo field" spectra by fitting each observed spectrum with a parametric model of Legendre polynomials optionally augmented with real spectra. Gains and offsets for every band are calculated by comparing the modeled spectra to the data spectra, for pixels that are well-fit. A number of spectra are used that span the entire albedo range to give good leverage for the linear regression process, and the data values versus modeled values are fit with a line for every band. The slope and offset of this line are used to correct the apparent reflectance data for the error features. You can apply gain-only corrections to fix the model-to-data offset to 0.

You can use one or more reality boost spectra (spectra from spectral libraries or field spectra) to help in the modeling. Using a few spectra that you know are characteristic of your area as reality boost spectra can produce better-fitting modeled spectra. The modeled spectra are created by a linear combination of the Legendre and reality boost spectra. Therefore, reality boost spectra that contain sharp features, such as the vegetation red edge, when used to augment the Legrendre basis set, can produce a better model, giving better EFFORT correction factors and/or offsets.

EFFORT works on one or more wavelength segments that you enter. Wavelengths ranges that contain only noise (for example, the 1.4 μm and 1.9 μm water vapor absorption bands) should not be used in the calculation.

Typically three segments are defined around the two large water vapor bands; bands before the 1.4 μm water vapor band, bands between the 1.4 and 1.9 μm water vapor bands, and bands past the 1.9 μm water vapor band. Each segment must start and end with a valid band. You can set bands within a segment that contain large, known errors but that are critical to further analysis as invalid, so they are not used in the initial spectral modeling.

Invalid bands may include overlapping spectral bands, bands with ringing around the 0.94 and 1.14 μm water vapor bands, and O2 and CO2 under-corrected or over-corrected bands. These invalid bands are not used in the modeling but will be corrected on output. The order of the Legendre polynomial that is used to model the spectra is set by you through trial and error (though the default value provided should work in most cases). You can model each segment with a different order polynomial.

Note: Select a polynomial order that will fit the real data features without fitting the error features. Before running EFFORT, use spectral plots of the radiance data to select the wavelength segments and invalid bands to input into the EFFORT dialog.

References

Huntington, J. F. and Boardman, J. W., 1995, Semi-quantitative Mineralogical and geological mapping with 1995 AVIRIS data, Proc. Spectral Sensing Research ‘95, ISSSR, Published by the AGPS, 26 Nov - 1 Dec, 1995, Melbourne, Australia.

Boardman, J. W., 1997, Mineralogic and geochemical mapping at Virginia City, Nevada using 1995 AVIRIS data, in Proceedings of the Twelfth Thematic Conference on Geological Remote Sensing, Environmental Research Institute of Michigan, Denver, CO, pp. 21-28.

Select EFFORT Input

  1. From the Toolbox, select Radiometric Correction > EFFORT Polishing. The Input File dialog appears.
  2. Select an input file and perform optional spatial subsetting, then click OK. The EFFORT Input Parameters dialog appears.
  3. Click Enter New Segment. A segment appears in the Segment Information list.
  4. Click Edit next to the new segment. The Segment Spectral Subset dialog appears with all bands highlighted by default.

  5. Select the starting and ending bands for this segment using Add Range; by clicking and dragging over the list of bands; or by clicking on the first band, holding down the Shift key, and clicking on the last band.

    To set bands contained within a segment to an invalid state so that they will not be used in computing the EFFORT correction, press the Ctrl key and click the bands to toggle them off. These data will not be adjusted and are set to 0. Invalid bands will not be used in the modeling, but they will be adjusted by EFFORT.

  6. Click OK.

  7. To change the order of the Legendre polynomial used to fit this segment, enter the desired order in the Order field next to the segment information.

    A lower-order polynomial produces a flatter spectrum, which gives more error suppression. However, it may also remove some actual reflectance features. A higher-order polynomial produces a spectrum that fits the data better but it also may fit some error features, which leaves them in the resulting output. To find a polynomial order that fits only real data, use a trial-and-error method.

  8. Enter new segments until all the spectral segments are defined.
  9. To remove the last segment entered, click Delete Last Segment.

Add Reality Boost Spectra

To input reality boost spectra:

  1. In the EFFORT Input Parameters dialog, click Input Reality Boost Spectra. An endmember collection dialog appears.
  2. Import the desired spectra. For details, see Endmember Options and Managing Endmember Spectra. The Reality Boost Spectra Options dialog appears.
  3. Toggle each Continuum Remove? to select whether or not to use a continuum removal on the reality boost spectrum.
    • To incorporate the spectral features and not the overall spectral shape, use continuum removal.
    • If the overall shape of the spectrum is important, (for example, vegetation spectra), do not use continuum removal.
  4. Click OK.
  5. In the EFFORT Input Parameters dialog, click Edit to change the reality boost spectra options, or click Delete to delete any of the input reality boost spectra.

Set EFFORT Parameters

Use the EFFORT Input Parameters dialog to set parameters for the EFFORT processing before executing EFFORT.

  1. In the Number of Points field, enter the total number of spectra to use in the EFFORT process. You should use at least 1,000 points, but no more than 10% of the total image size.
  2. Enter a value for Albedo Bins to divide the albedo range into and select spectra from. The number of spectra used in each albedo bin is the total number of points divided by the number of albedo bins. This ensures that spectra with a range of albedo are used in the modeling.
  3. Toggle EFFORT Calculation to calculate gain and offset values or gain values only.
    • To correct your data for gain values only, select Gain. These include errors in the radiometric calibration, atmospheric transmittance model, and solar irradiance model.
    • To correct your data for both gain error and offset error, which include errors in the dark current and path radiance model, select Gain and Offset.
    • To save the gain and offset values to an ASCII file, specify a filename in the Enter Output Gainoff Filename [.txt] field.
  4. Click the Apply Results? toggle button to apply the calculated gain and offset values to the input data.
    • If you select No, the gain and offset values appear in a plot window when you click OK in the EFFORT Input Parameters dialog, and no other output will be generated.
    • If you select Yes, select output to File or Memory. The gain and offset values appear in a plot window when you click OK in the EFFORT Input Parameters dialog, and an EFFORT-corrected apparent reflectance output file is created, using the filename you specify in Enter Output Filename.
    • To overwrite the input file with the EFFORT output, set the In Place? toggle button to Yes. Note that you cannot interrupt this process without corrupting the input data file.
  5. Click OK. The processing is completed in three steps, shown by three status processing dialogs. ENVI adds the resulting output to the Layer Manager, and the gain and offset values appear in a plot window.