Even though we have had great success with the Canon and Casio continuous shooting**, high speed cameras for getting high image overlap, we are still having issues with image exposure. I purchased a Lastolite EzyBalance camera calibration card from Service Photo in Baltimore as way to systematically deal with these issues.
When in continuous shooting mode, the cameras make calculations for focus and exposure based on the first photo taken when the button is pressed (Canon SD4000 Camera Manual). This means that all photos in the scene will have an exposure (under-, over-, or “correct”) based on the lighting conditions of the first photo. We discovered this when first using these cameras on the Slow Sticks. When attaching the camera to the underside of the plane frame, the camera is pointed up at the sky and sun. When the continuous shooting mode is activated the camera records the light conditions as if it were receiving direct light from the sky/sun. When the plane is turned right side-up less light is entering the lens and so the photos are underexposed, too dark. If I mount the camera and activate continuous shooting mode with the camera pointed at the ground it will record lower lighting conditions than what will be observed at altitude above the canopy, so the photos are overexposed, too light.
I am still learning about how SIFT and computer vision work and we are just now at the point where we can start to test changes in camera settings, but based on some preliminary research I think it will be important to strive for consistent illumination among images. SIFT is largely invariant to changes in illumination between images, so it should still be possible to match photos of the same place under slightly varying illumination conditions (Lowe 1999).*** Since the camera settings are consistent between photos, there should not be changes in feature illumination between photos for the same image collection, unless clouds move into the scene during the flight. However, under- or over- exposed images may result in a reduction in the detection of image features. Many things to be tested for sure, but I want to start with trying to achieve consistent image illumination.
Here are some simple examples of my backyard for illustration. I used the open-source GIMP image editor to generate the image intensity histograms for each image. The interpretation of image intensity histograms is somewhat subjective or scene based, but the examples below merely serve as illustration of the value of the cal panel.
The image on the left is over-exposed and the image on the right is under-exposed. Prior to setting the camera into continuous shooting mode I pointed the lens down at the shadow of my body at my feet and then out across my lawn, resulting in the over-exposed image at left. For the right image I started with the camera pointed up at the sun and then down to my lawn, resulting in under-exposure. The left histogram is so white that almost all values are at the far right end of the chart and are hard to see. The right histogram has values clumped at the left side, representing darker values throughout the whole scene. In either image it is difficult to make out features, for example the grass in shadow at the right side of the right image, and of course nothing is visible in the left image.
By photographing a fully illuminated grey calibration panel first I get a resulting image with much more natural looking and distributed color intensity, as can be seen in the image at right. This more spread out histogram is interpreted as having more tonal variation. While we still have lots to test about camera settings, the goal is that by using this cal panel prior to flight we will be able to achieve consistent photo illumination and exposure. There are other panels with black, grey and white that can be used to deliberately cause images to be under or over exposed, e.g., the Lastolite XpoBalanceused by some to calibrate digital photos for portraits and also for calibrating the intensity of LiDAR beams (Vain et al. 2009).
OK, that’s enough. It is too beautiful out to drag this post along any more!
** I just discovered a ‘low-light’ 2.5MP resolution camera setting that makes it possible to achieve 5 photos per second with the Canon SD4000, wow! This has the effect of increasing the camera ISO which may result in grainy photos under high illumination and it is not possible to change that resolution setting.
*** Thanks to my Computational Photography course that I am taking this semester, my review of the Lowe SIFT paper for this post finally made sense!
refs:
Lowe, D.G. 1999. Object recognition from local scale-invariant features. In International Conference
on Computer Vision, Corfu, Greece, pp. 1150-1157.
Vain A., Kaasalainen S., Pyysalo U., Krooks A., Litkey P. Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data. Sensors. 2009; 9(4):2780-2796.