Leica digital camera processing

The RCD produces raw files that need to be processed in order to create TIFF files. See the RCD page for instrument details, including filename convention.

Raw to Tiff

The first stage in processing the photographic data is to convert the raw file format into a 16-bit tiff format. The procedure for processing raw images to tif images can be found here.

Post-processing

1. Get a camera .sol file
   • Check there is a *_camera.sol file in the IPAS/proc directory. If there is not, then you will need to create one. See details here
2. Remove "bad" images
   • Create temporary thumbnail images of the processed tiff files using photo2thumb.sh.
   • Open the first image with eog and use either spacebar to scroll though the images or view/slideshow. Remove the corresponding tiff images for any that are over/under exposed.
3. Remove images that don't correspond to flightlines
   • Create a temporary kml file: kmlise_project.py -d <main_project_dir> -e ***ImageEvents1.csv > kml_file.kml Make sure the correct eventfile is being pointed to NOTE- this program currently falls over unless the eagle directory is clear of unrecognised files
   • Open the kml file in google earth
   • Note which blocks of photographs do not overlap with any Eagle/Hawk data. Usually consists of a group of photographs at the start of the survey where they set up the exposure rates etc for the camera. Often the log sheet notes which images too. Delete these tif files (not the raws) since they are not required.
   • Delete the kml file created above as it is no longer needed (an updated one will be created by the delivery script)
4. Create a new image event file with post-processed positional data and omega,phi,kappa values
   • Open IPAS CO (on the windows machine)
   • Load in the *_camera.sol file and from rcd/logs the *!ImageEvents1.csv and *!PhotoId1.csv file
   • Camera Orientation Direction: -90
   • Event Offset: 0.006
   • Output file as *!ImageEvents1-processed.csv, file format ASCII Output
5. Check the event log file for erroneous entries
   • If there is no log file then you will need to look here for information on tagging without log files.
   • Anything with a -1 in GPS time will not be able to be tagged fully, but only with project information data. If possible, you might be able to use the SensorStats log file to estimate the GPS time of the erroneous events. Use the time differences in the log file to estimate the GPS time. Note down any image names you do this to so that it can be put in the Read Me. This is probably no longer worth doing - seems to be too imprecise

Delivery Script

The script incorporates:

• Tagging the images with positional and navigational data as well as project information
• Renaming the images to conform to ARSF standards
• Generating thumbnail images of the tiffs
• Creating the final kml
• Making final version of the eventfile, including removing any lines referring to photos you have removed
• Creating and populating delivery directory

Run:

make_camera_delivery.py -p <main_project_dir> -e <event_file>

Check the output then run with --final option.

If the script fails then you will have to fix the problem and try again, or follow the individual stages listed here. Possible causes of failure, excluding the ones previously mentioned above, could be:

• SOL file GPS times do not overlap with photograph log file times. Either fix the SOL (if possible) else use the logfile to tag the images (and mention in the Read_Me)

Creating the Read me

• The above script will generate a config file for the latex PDF script. If it fails for some reason then run generate_readme_config.py with the -d option (giving the delivery directory) and "-r camera" as airborne.
• Edit the config (should be located in processing directory). Remember to add information on any photos which could not be tagged fully, or any images which look like they have anomalies or over/under exposure. To add new line characters enter '
  '. Tagtype should be "full" if photos have been tagged with pos/att information or "min" if only tagged with project details. If both types are present in the delivery then use full and in the "data_quality_remarks" section add a sentence explaining which photos have been unable to be tagged with pos/att and why. Line_numbering should contain a space separated list of names/numbers identifying flight lines.
• Create the LaTeX TeX file. To create the TeX file use the script create_latex_camera_readme.py with the -f option, giving the location of the config file generated above. This is editable in any text editor and can be manually edited to correct mistakes or insert new text
• Convert the TeX file into a PDF file. This is done using the command latex <TeXFile> and should create a file named Read_me-TODAYSDATE.pdf. It is advisable to keep the TeX file somewhere safe until after the delivery has been checked in case some changes to the Read_me need to be made (the TeX file should not be part of the delivery).

Subsequent processing ideas

There are several other steps that could be undertaken in the future:

• orthorectification (map the photos with respect to the ground/aircraft position)
• geocorrection (map the photos with respect to the ground + a DEM) - possibly only Bill's azgcorr mods could do this
• compositing orthorectified photos and seam-line adjustment
  • compositing is easy, but will have ugly problems when you get different views on an object with vertical structure
  • to improve the look of this, you have to manually edit the positioning of the joins - this is currently a very manual process and we do not currently have software for it