This tool performs a refined RPC orthorectification using a digital surface model (DSM) created from a dense image-matching algorithm. A DSM represents the earth's surface and models all objects on it. It provides a higher resolution source of elevation data, compared to traditional digital elevation models (DEMs) such as GMTED2010. It significantly improves the accuracy of RPC orthorectification.

Note: This tool runs on Windows 64-bit platforms only.

You can also write a script to perform RPC orthorectification using the RPCOrthorectificationUsingDSMFromDenseImageMatching task.

The DSM is generated from two or more images taken from different view points, and it is used as the terrain source to orthorectify the first raster in the input rasters. For best results, put the raster closest to nadir view first.

The dense image-matching algorithm identifies corresponding points in at least two images. For a given point in one image, it searches a two-dimensional grid of points in the second image. By having orientation data, the search is reduced to one dimension: along an epipolar line in the second image. The success of the algorithm depends on the intersection angle and similarity between the images. A good starting point is to use images from the same season during a given year.

This tool has been tested with the following types of stereo imagery:

  • ADS-80 (physical sensor model)
  • ENVI format with a generic RPC sensor model
  • GeoEye-1 in DigitalGlobe format (.til) and PVL format
  • Pleiades-1A
  • QuickBird
  • SPOT-6
  • WorldView-1
  • WorldView-2
  • WorldView-3
  • Ziyuan-3A

Follow these steps:

  1. From the Toolbox, select Geometric Correction > Orthorectification > RPC Orthorectification Using DSM from Dense Image Matching.
  2. Select two or more input rasters:
    • They should have enough parallax, for example, stereo and tri-stereo images collected by sensors from different view points.
    • They must overlap by at least the percentage specified in the Minimum Overlap parameter. The default value is 55 percent.
    • They must contain rational polynomial coefficients (RPCs) or physical sensor models. For satellite images, RPCs are preferred over physical models.
    • They must have the same number of bands. Select two or more panchromatic datasets, or select two or more multispectral datasets that have the same number of bands.
    • For other sensors not listed above, open the individual image files (TIFF, JPEG2000, or NITF) if available.
  3. Select whether or not to perform a Block Adjustment before creating the DSM. A block, or bundle, adjustment is used to refine the 3D coordinates that describe the scene geometry. It finds a set of parameters that most accurately predict the locations of the observed points in a set of images, thus minimizing the reprojection error between image locations of observed and predicted image points. Applying a block adjustment for satellite images refines the image geometry to improve the quality of the DSM. If the the images have already been adjusted, disable this option.
  4. Enter a Minimum Overlap percentage (0 to 100), indicating the minimum overlap area between two images, for matching to occur. Image pairs with a smaller overlap than the specified value are ignored. The default value is 55 percent overlap.
  5. Enter a Matching Threshold value. The match threshold sets a limit to the difference between matching windows. A value of 0 means no difference (a perfect match). Set this property to a lower value to increase confidence and to decrease mismatches. Set it to a higher value to capture finer details at the possible cost of more mismatches. The default value is 15.
  6. Specify an Edge Threshold value between 0 and 100. Set a lower value to include more mismatches in areas with poor contrast. Set a higher value to force rich texture and edge information in accepted matches. The default value is 5.
  7. Enter a Quality Threshold value between 0 and 100. Each pixel is assigned a quality measure, which is based on the similarity between windows around the pixel in the stereo images at the matched position. Setting this threshold to 0 will export all matched points for DSM generation. Increasing the threshold exports fewer matching points, but the quality of the DSM is potentially better.
  8. The Output Coordinate System field lists the default projection (UTM) for the orthorectified image.
    • To change it, click the Browse button and select a different coordinate system.
    • Click the From Dataset button to use the coordinate system of en existing raster dataset.
    • Click the Current View button to use the coordinate system established in the current view.
    • Click the Reset button to clear the Output Coordinate System field.
  9. Enter an Output Pixel Size in the X and Y direction in meters. The default value is derived from the pixel size of the input image.
  10. Select an Image Resampling technique from the drop-down list:
    • Nearest Neighbor: Uses the nearest pixel without any interpolation.
    • Bilinear: (default) Performs a linear interpolation using four pixels to resample.
    • Cubic Convolution: Uses 16 pixels to approximate the sinc function using cubic polynomials to resample the image.
  11. Enter an Grid Spacing value. This value represents the grid spacing in output pixels, for which ENVI finds the corresponding pixels in the input images through an RPC-based transform. With a coarse grid, the RPC orthorectification is faster but less accurate. The default value is 10. A value of 1 is for a rigorous orthorectification when you have a high-resolution DEM and the study area has lots of terrain relief.
  12. Enter an Output Raster filename and location for the orthorectified result.
  13. Enter an Output DSM Raster filename and location for the generated DSM.
  14. Enable the Display result check box to display the orthorectified image and the DSM in the Image window when processing is complete. Otherwise, if the check box is disabled, image can be loaded from the Data Manager.
  15. To run the process on a local or remote ENVI Server, click the down arrow and select Run Task in the Background or Run Task on remote ENVI Server name. 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 the ENVI Servers topic in ENVI Help for more information.
  16. 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.