Comparing Rosco infrablue filters #2007 vs #74 for NDVI imaging

I am comparing here the results obtained with this two Rosco filters when getting NDVI images from NIR photos. The camera used was a Canon A490 with the IR filter previously removed. Camera was white balanced with a blue origami paper before taking photos with each filter. The software to process NIR photos was Fiji and Photomonitoring plugin.

The ideal criteria would be to compare NDVI values with real biological plant data, but as this is not possible for me I would compare photo histograms, that is objective data, and then interpret NDVI image, a more subjective analaysis.

Firstly it is interesting to compare filter spectral response. #74 lets less green wavelengths pass through and a bit less energy from blue channel, also less NIR wavelengths (> 700nm), so we can expect greater red-blue channel differences with #2007. The total area of passing wavelengths seems greater for #2007 so it will generate more luminous photos.

#74 filter above, #2007 below

This photo contains some plants and also some other objects that are not photosynthetic, I took this photo to evaluate filter ability to distinguish photosynthetic materia in an image.

The deduction about amount of light seems true as camera used faster shutter time for #2007. One curious thing is that leaf shadows appear with higher ndvi level than leafs, specially with #74. And also the shadow that crosses all the stone circle is noticeable in the #74 NDVI image, but not in the #2007. So one conclusion from this is that #74 is more affected by shadows and could lead to errors when distinguising plants in one image.

The histogram of each photo is the following. The difference between the average values of red and blue channel is 28,4 for #74 and 26,2 for #2007, what is not what I expected, but this full image histogram is not very meaningful as more than 75% of the photo is non photosynthetic material and the amount of plant reflecting more NIR is small. Anyhow I am comparing average values for each channel, which is a very rough analysis.

This other image is from just some leafs, all the objects in the image are photosynthetic so here we can evaluate better the ability of each filter to differentiate ndvi levels.

The histogram of the image reveals now a R-B everage difference of 62,1 with #74 and 56,2 for #2007. Here the comparison is for a image with 95% of photosynthetic material. And this small difference in channel levels is noticeable in the NDVI image, as the different levels in the main leaf are more clear in the #74 than in the #2007. 

The first conclusion is that #74 performs a bit better for my Canon A490 CCD, I will soon try the red filters as it is commented at Infragram that performs better than blue ones.

Getting good NDVI data from NIR infrablue aerial image

This aerial image was taken with a Canon A490 with the IR filter removed and with a piece of Rosco #2007 filter attached.

Exposure time: 1/1250"
F4.5
ISO 160

Focus: Single Point AF

Aerial image at 150m

I am testing this CHDK script for automatic exposure control, in the parameters you set a range of ISO, Av and Tv and the script calculates the best option at each photo. The only tricky issue with this script is that the lock focus and set focus to infinity doesn't work the same way on all cameras and if you are not lucky and the standard code doesn't work for you then you will have to figure out which are the right commands for your camera. I tested setting focus lock to infinity and also disabling lock focus and leaving the camera standard auto focus at each photo, and was getting better results with AF for my quad, camera, landscape configuration so I used that.

The purpose is to get a NDVI image and some insights on how proceed to get the best results given a set of amateur resources.

Rosco #2007 Infrablue filter

This infrablue filter is referred at Infragram to get better results with CCD cameras, although the results vary depending on the camera sensor (spectral response to NIR), camera settings (ISO, Av, Tv)  and white balance. I am using a custom white balance calibrated with a piece of blue origami paper, that is proven to get better results.

Rosco #2007 filter

Analyzing the color histogram of the photo can give us a hint of the quality of the resulting NDVI data. As NDVI is calculated from the difference of Red (NIR) and Blue channels, the separation between these two channels in the histogram is the key reference. For same scenario, the settings that get better separation os channels will likely get a more meaningful NDVI image. The main variables you can play with are:

- infrablue filter

- camera ISO, Av, Tv

- white balance

This is the color histogram of the entire image, that predicts a relatively good ndvi data as red and blue channels are at least well differenciated.

Color histogram from full image

This is the color histogram of just one tree (marked at the image with a yellow square), where the difference between the blue and red levels is more noticeable:

Tree selected for color histogram

Color histogram from one tree

NDVI images

This are the NDVI images obtained using Fiji and PhotoMonitoring plugin, the color difference between them is the lut used to map NDVI float values to color.

NDVI using NDVIBlu2Red lut from photomonitoring plugin

NDVI with special lut

Conclusions

1. Using a filter means that less light is reaching the sensor, and  that it will need longer exposure time to get the same energy, so Av and ISO should take this into account to get the shortest shutter speed and a clear photo. To get the same amount of light in less time lower F and higher ISO will help, but maintaining a reasonable range to avoid problems with too low F(too large deep of field, normally in aerial image we want the focus just in the ground) of too high ISO (noise). This image can help to understand:

This CHDK script can help you to get the best values for your specific situation: camera, ilumination, landscape colors, filter and uav performance about vibrations, but at the time of getting photos for a mosaic these values should be static, specially for getting a good NDVI mosaic where ndvi values can be compared between points that comes from different photos.

2. From the settings that influence the quality of the NDVI image, the only one that can be modified a posteriori is the white balance, and that just when you get a raw photo, so shooting raw will let us achieve better results. The downside of this is that taking the raw means more time between photo and photo, and that will impose a limit in your photo interval and then in the flight plan.

3. You can play with the lut to get the best  result according to the ndvi image purpose, from the above ones you can see that with the special one a best differentiation of live/dead object is seen.

4. Each camera will get better results with different filter, so you can take a know good combination of both or experiment by yourself.

5. White balance is critical to get good NDVI data, getting the best calibration of custom white balance is the key, and that depends on the light source at the momment of getting the photo, so this is something that should be done in situ before placing the camera in the uav.