Vexcel’s UltraCam digital camera system has a focal distance of approximately 100mm and offers a base panchromatic (black and white) resolution of 11,500 x 7,500 pixels, along with four color channels: red, green, blue (RGB) and near-infrared. Forward motion compensation can support pixels as small as three centimeters on the ground.
The UltraCam features imagery with a better than 12-bit per pixel dynamic range. This improves the radiometry for better matching accuracy, allowing for more flying days in marginal weather as well as better interpretability, better stereo, and more success in automated procedures.
PCI Geomatica supports UltraCam L3 type of images. This tutorial will demonstrate the processing steps of UltraCam L3 images in Geomatica OrthoEngine.
1. Initial Project Setup
Start OrthoEngine and click ‘New” on the File menu to start a new project. Give your project a ‘Filename’, ‘Name’ and ‘Description’. Select ‘Aerial Photography’ as the Math Modeling Method. Under Options, select ‘Camera Type’ as ‘Digital / Video’ and ‘Exterior Orientation’ as ‘User Input’. Exterior orientation is selected as User Input, if GPS/INS information is available from digital camera. Otherwise select ‘Compute from GCPs and Tie Points’ and the math model will be calculated from user entered GCPs and TPs.
After accepting this panel you will be prompted to set up the projection information for the output files and the output pixel spacing. Enter the appropriate projection information for your project.
2. Camera Calibration
OrthoEngine will automatically prompt you to enter ‘Digital Camera Calibration Information’ after the projection information step above.
Camera Calibration information is generally provided with your digital aerial dataset. Check support files of your UltraCam dataset and enter the appropriate camera calibration information in OrthoEngine.
Principal point offset value can be calculated as:
Principal Point of Symmetry (POS) + Principal Point of Autocollamation (PPA) – Indicated Principal Point (IPP)
Principal point offset for a DMC camera is usually zero.
Note: DMC digital camera air photos can be processed using the exact same steps as UltraCam except for the ‘Camera Calibration’ information. Camera calibration parameters of DMC and UltraCam are distinct.
The images below show demo Camera Calibration panels for UltraCam and DMC digital cameras.
UltraCam Digital Camera Calibration (below)
Digital Camera Calibration (below)
3. Data Input
Go to the ‘Data Input’ processing step and click ‘Open a new or existing image’ button.
Add your air photos using the ‘New Image’ option in the ‘Open Image’ panel. You will then be prompted to create overviews for your images. Please note this could take a few minutes.
4. Exterior Orientation
Exterior orientation represents a transformation from a ground co-ordinate system to image co-ordinate system. In other words, exterior orientation is the position and orientation of the camera when the image was taken. Most photogrammetric cameras are equipped with onboard GPS and Inertial Navigation System (INS). These systems collect the exterior orientation directly on the plane and ship this information with a digital dataset.
Exterior Orientation can be either imported using GPS/INS data or can be computed from GCPs and Tie Points. If you are using GCPs and TPs to compute exterior orientation, then adding estimated or observed exterior orientation to your project can reduce the number of GCPs required. It also helps to automate the tie point collection and it decreases the time needed to setup the project because it provides an approximate location of the images.
In this project we will import GPS/INS data from an external file. In the ‘Data Input’ processing step, click on ‘Import exterior orientation data from text file’ to pop-up the import window.
Select the appropriate ‘File Format’ according to the format of your GPS/INS file and import the text file into the OrthoEngine project. If you need to edit the exterior orientation information before processing the images, use the ‘Manually edit exterior orientation data’ window on the OrthoEngine toolbar under the ‘Data Input’ processing step.
5. Collect GCP’s and Tie Points
This step is valid only if exterior orientation is selected as ‘Compute from GCPs and Tie Points’ during the initial project setup.
Select the ‘GCP/TP Collection’ processing step. GCP collection can be done using various options viz. ‘Manual Entry’, ‘Geocoded Images/Vectors’, ‘Chip Database’ or a ‘Text File’.
For Aerial photographs 3 GCPs per image are recommended for highest accuracy. Tie Points are usually collected in a typical Von Gruber pattern of 3X3 points per image. Users should try to add good quality GCPs and TPs. Features that are closer to the ground should be selected as TPs instead of selecting features like tree tops, shadows etc. Tie points that join multiple images together produce a more accurate math model. Also, if available, enter the elevation value of the tie points in your project. Tie points with an elevation value help to control elevation errors and improve the accuracy of the geometric model.
After GCP and TP collection, click the ‘Compute Model’ button under ‘Model Calculations’ processing step. This will compute the math model for your Air photo OrthoEngine project.
6. Generating Orthos
The next step is to set up your ‘Ortho Image Production’. Proceed to the ‘Ortho Generation’ processing step in the OrthoEngine toolbar. Select ‘Schedule ortho generation’.
In the Ortho Image Production window select the images to process. Choose the DEM file to be used in the processing, and other processing parameters. Click on ‘Generate Orthos’ to create the final orthorectified air photo.
Images below show individual orthorectified air photos.
The final step is to generate a mosaic of your orthorectified air photos. OrthoEngine provides an option of manual as well as automatic mosaicking. Based on the size of the dataset, manual mosaicking could be very difficult and time consuming. In this project we will perform automatic mosaicking of the above orthorectified air photos.
In the OrthoEngine toolbar select ‘Mosaic’ as the processing step. Select ‘Define mosaic area’ to create a blank mosaic file.
In the Define Mosaic window, enter an output mosaic file name and select the footprint of the air photos. Click OK to close the define mosaic window.
In the OrthoEngine toolbar select ‘Automatic Mosaic Generation’. Set the mosaicking parameters appropriately and click ‘Generate Mosaic’. An automatic cut line generation and color balancing is performed internally before mosaicking the images.
Note: This level of accuracy of each individual ortho – features which are on the ground (roads, vehicles, etc) align perfectly between the two adjacent images. Building lean and other artifacts created by elevated features can be removed through automated cutline generation and editing. PCI’s tools for creating and editing cutlines are quite powerful.