Question: How can I make IR photos derived from various cutoff useful for creating NDVI (normalized difference vegetation index) images?

Thank you, Chris, for helping to clarify my question. In fact, as you suspected, I was misusing the term "bandpass"! Those I signify with a "K" followed by a 3-digit number are all, to my knowledge, cutoff filters, where as the other three I currently own are bandpass filters.

Upon revisiting the question I posed, I now see how I can refine it to make it less vague; however, I am new to this forum and don't know how to revise it without just posting an entirely new question. Does anyone know how?

My revised question would read as follows: How can I make IR photos derived from various cutoff filters useful for creating NDVI (normalized difference vegetation index) images?

If your K610 filter is a cutoff filter that passes wavelengths greater than 610nm and blocks shorter wavelengths, then it is similar to many filters used to make NDVI images. These red filters on a full spectrum camera (no IR cut filter) will record mostly NIR in the blue channel and red plus some NIR in the red channel. The values from the blue channel can be used as a measure of NIR brightness and the values in the red channel can be used as a measure of red brightness. There are two reasons that the recorded ratio of red to NIR will not be similar to that of the light reflecting off the scene. The red channel is somewhat inflated because it contains some NIR, and typical sensors are much less sensitive to NIR than to red. To correct that error a calibration procedure can adjust the levels. A much simpler correction is to boost the blue signal by some arbitrary factor. A proven hack with some cameras and filters is to fool the camera by using the custom white balance feature to exaggerate the blue brightness. Point the camera at something very red in direct sunlight and push the custom white balance button. If the camera allows this highly artificial color balance, photos taken in daylight of healthy vegetation will be turquoise and can be used to derive NDVI images.

The general principles are described here: https://publiclab.org/wiki/ndvi-plots-ir-kit

Chris

If you can find the edit button on your post (pencil icon) you can edit anything in the post.

Thank you so much, Chris! With respect to what to use as a reference to calibrate the White Balance (WB), I have not yet "digested" whether your recommendation is confusing or clear, but what I have been doing in general for WB calibration is as follows, always with the external filter of interest already attached:

1. If the filter includes any portion of the visible light (abbrev. VZ) spectrum to pass to the image sensor, I employ an 18% gray cloth for calibration;

2. If the filter passes light only with wavelengths greater than 700 nm, then I calibrate to a chlorophyll-containing structure, e.g. green grass or a healthy leaf.

What do you see are the pitfalls of my approach to WB calibration, whether in general or with specific respect to optimizing WB for NDVI images?

The goal of the custom white balance hack is to fool the camera into wildly exaggerating the brightness of the blue channel (when using a red filter). The result is that the values used for NIR in NDVI computations will be a few times greater than otherwise.

Using a grey card (18%) will not alter the default blue:red ratio very much if at all. By definition, grey has about the same amount of red and blue.

Chlorophyll reflects both red and blue light, and will not alter the blue:red ratio very much.

Neither of those white balance settings will produce photos very different from any of the standard white balance choices (sun, shade, tungsten, fluorescent).

Finding the proper color surface for a custom white balance is tricky because the amount of NIR reflected from it matters and NIR is invisible to us and therefore does not affect the color we see.

Check out this note: https://publiclab.org/notes/claytonb/08-13-2016/plant-health-ndvi-white-balance

Chris

Using green foliage (or chlorophyll) to set a custom white balance deserves more consideration than I gave it in my last comment. Foliage absorbs roughly about half of the blue light and a quarter of the red light hitting the leaves. So roughly half of the blue light and 75% of the red light might be reflected back to the camera.

When a custom white balance is done with a full spectrum camera with red filter (e.g., your K610) NIR light must also be considered. Foliage reflects almost all of the NIR hitting it, so lots of NIR will come back to the camera.

The blue channel will not get much blue light because the red filter blocks it, but lots of NIR will be recorded in the blue channel. The red channel will record both the red and NIR reflected from the foliage. The red channel is often more sensitive to NIR than the blue channel is.

So the red channel will record more brightness than the blue channel which is exactly what the custom white balance procedure needs in order to exaggerate the blue channel values. So pointing the camera at foliage in daylight during the custom white balance procedure will push the results in the right direction. It probably will not push the results far enough to produce NDVI values in the correct range, but the results could be interpretable.

Instead of using foliage, using a surface that reflects lots of red, no blue, and no NIR will do more to exaggerate the blue channel values. When the custom white balance algorithm sees all that brightness in the red channel and none in the blue, it will adjust every photo by exaggerating the blue channel values.

We generally don't know how much NIR is being reflected from a colored surface, so choosing a useful surface can involve some trial and error. However, with a full spectrum camera and your K720 filter (assuming that filter passes only NIR) you can easily determine the relative NIR reflection from various surfaces. The goal should be to find a surface that is reddish but reflects no NIR, although some NIR reflection does not necessarily disqualify a surface.

This process is different from a calibration procedure which adjusts the red and blue values based on photos of targets of known reflectivity and compensation for the contamination of the red channel with NIR. Compared to calibration, this process is a clever hack which can produce potentially useful results.

Chris

Thank you, Chris! You've given me much to read and think about, but please, don't misconstrue that as meaning you shouldn't add any additional pertinent information. - lev29