OV5647 spectral response

In order to use the raspberry pi cameras within a more rigorous framework I needed the full spectral response of the chipset used in these cameras, the OV5647 by OmniVision. I set out to do acquire the response curves using a DIY diffraction grating approach.

During this process I was contacted by Howard Shapiro who volunteered his old spectrofluorometer to accomplish this task faster and more precisely. Although, initial tests together with Howard showed promise, it would remain an arduous task to quantify the whole spectral response. Recently, Howard managed to dig up
some documentation on the chipset which displayed the spectral response (quantum efficiency, QE) in a graph (given that the OmniBSI chipset as displayed is the one residing in the OV5647). This has made things considerably easier. I used these slides to digitize the quantum efficiency of the OV5647 between 400 and 700 nm. A physical measurement will still be needed to quantify the remaining near infrared spectrum (> 700 nm, data can be found on the OV5647 spectral response page).

Sadly, the original graph only covers wavelenghts between 400 and 700 nm, leaving out the near infrared (NIR) part of the spectrum. The red edge, located at 680-730nm, is a key part of the spectrum key in vegetation remote sensing applications. At the red edge vegetation reflectance changes from low to higher values. The magnitude of this differences is an indication of plant health.

Although I got most of the picture, due to good detecitve work by Howard, I still don’t have the complete picture. Some physical measurements will still be necessary to get the complete spectral response / QE of the chip but I’m at least halfway there.

2 Replies to “OV5647 spectral response”

  1. Hey Koen, just read this post and noticed your comment about magnitude of plant reflectance indicating vegetative health. I was curious how this works. Is a large difference in magnitude indicative of good or poor health? I used a spectrophotometer for my masters work but never did get to learn exactly what the principals for remote sensing are outside of hearing a handful of talks…

    1. The rational is that most photosynthetically useful radiation is situated below 700nm. This part of the spectrum caries enough energy to power photochemical reactions. Moving beyond 700nm into longer wavelengths, into the near infrared (NIR), you only generate heat without gaining energy to drive a chemical process. This heat can damage plants, so most of this is reflected (not absorbed). Furthermore, the more leaves you have the more you scatter infrared light as well. Therefore, infrared pictures of plants they always light up brightly. These differences in absorption / reflectance are used to calculate a plant’s physical appearance and/or health.

      The normalized difference vegetation index (NDVI) exploits both the relation to changes in pigments (<700nm, VIS) as well as vegetation structure (>700nm, NIR) to come up with a measure of plant health / active vegetation cover.

      NDVI = (NIR – VIS) / (NIR + VIS)

      a simple ratio (SR) between NIR / VIS would conceptually do the trick as well. In both cases the difference between the NIR and VIS values gives you an idea of how the plant is doing. If the plant does not change structurally but only loses pigment (absorption in the VIS) your index will decrease as your VIS value will increase (less absorption is more reflectance, which yo measure). However, unlike the SR the relationship between the NDVI and for example biophysical parameters such as biomass is stronger and therefore has seen more widespread use compared to a simple ratio.

      More details are here: http://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index

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