Image above: False color infrared (NBG) image from an infrablue photo taken from a commercial airliner. Scene is looking south near Delta, Alaska at the dendritic erosional pattern of loess covered hills. Reddish patches are birch and aspen trees on the mostly south-facing slopes. North facing slopes are dominated by permafrost and support stunted muskeg and black spruce forests.
The comparison below demonstrates why NDVI is usually computed using a value for the visible red wavelengths instead of blue for each pixel. Red light is not scattered by air and water vapor as much as blue light and makes a crisper image especially when the air is hazy. Infrablue photos use the red channel for infrared light, so must rely on the blue channel for the values for visible light when computing NDVI. The amount of scattering depends on how much air the light passes through, so for aerial imaging the haze effect increases with camera altitude. For oblique aerial photos, this produces a gradient of increasing bluishness with distance. When the blue channel is used for values of visible light in NDVI calculations for oblique aerials, this produces an artifactual gradient of decreasing values with distance. Two-camera systems which use the red channel from an unmodified camera for the visible light data are less subject to this artifact.
The gigapan embedded below can be seen here: http://www.gigapan.com/gigapans/133294/
Scenes above are looking north at the eastern shoreline of Lake Huron. The infrablue camera was a Canon A810 with Rosco #74 filter (no IR block filter). The RGB camera was a Canon S95. The NIR camera was a Canon A495 with a Wratten 87 filter (no IR block filter). The red channel is primarily near infrared light in the infrablue photo, primarily visible red light in the RGB photo, and all near infrared light in the NIR photo (the Wratten 87 filter passes almost no visible light). The NRG image is made from the infrablue photo and is really NBG. By stretching the histogram of the infrablue photo (Photoshop/levels), the range of NDVI values with distance is reduced (the gradient becomes steeper?).
2 Comments
@cfastie What do you mean with 'stretching the histogram of the infrablue photo'? Because if it means to reduce blue levels (increase NDVI levels), why doesn't appear the pinky zone in the streched image with respect to the non-streched?
Another doubt: What's the difference between an Infrablue photo and a NGB photo? I thought they were the same. I say it because of the bottom left image (in the text you explain that's a NBG photo obtained from the Infrablue photo).
Thanks!
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Stretching the histograms of either the NIR or VIS (or both) channels used to make NDVI is a trick that can produce more meaningful NDVI. I don't know why it works, and sometimes it does not work. Stretching the histogram means rescaling the brightness values for one channel in all of the pixels in an image. Instead of the values for red being between 150 and 220, after stretching the values will range from 0 to 255. This has different affects on different photos. Sometimes stretching one or the other channel works great, sometimes stretching both makes better NDVI images. Ned's photo monitoring Fiji plugin has an option to stretch one or both histograms.
An infrablue photo can be called NGB. Ideally, a photo taken with a camera with the IR block filter replaced with a blue filter that blocks all red will have only NIR in the red channel and the other channels will be dominated by either green or blue as they usually are. So it is NGB instead of RGB. An NBG image can be made from such a photo by swapping the blue and green channels. That makes an image that looks superficially like traditional false color IR photos which are called NRG -- NIR in the red channel, Red in the green channel, and Green in the blue channel. Better NRG images can be made from red filtered NDVI cameras because the red and green channels are available for this (infrablue photos use the red channel for NIR). Even better NRG images can be made from orange filtered NDVI cameras because the green channel actually records some green light: http://publiclab.org/notes/cfastie/01-16-2015/orange-is-the-new-red.
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