Long-exposure with Raspberry Pi at night

Question

I am working on a project that requires multiple photos of a specific building at night. I want to set up a webcam and a Rasperry Pi, and set it to take an image every 30 Minutes every night for a few months. From these pictures, I will extract the shape of the building, and calculate the difference in illumination between the building and the background. This doesn't need to be super precise, since I will use averages over time.

I have a Rasperry Pi 3, and am looking to purchase a fitting webcam. There are two common camera modules available, one with, one without IR filter. For night time photography, the IR-Version is usually recommended, but if I understand it correctly, those require IR illumination. Since we are talking about a building, illumination is off the table. Since the amount of light is my entire focus, I do not need the images be good, or even sharp. Just consistent.

Now I have the following questions:

• Does a Non-IR-Filter-Camera make sense for this project, or should I rather stick with the normal camera module?

• The maximum shutter speed for the Raspberry Pi camera module seems to be 6 seconds. I have not found any hardware documents for this, so can anyone confirm this?

• Is this even a viable setup, or am I missing anything fundamental?

Answer 1

An IR filter reduces a portion of visible light as well. You would do well to ask for the transmission curves at the camera detector with and without the filter. Determine what spectral range you need to cover in your "light" and "background" regions. By example, when you cannot accept that an IR filter will cut 10% of the visible dark red region of your image because you want to include the true color intensity of neon red signs in the images, then you have your answer.

Since you seem to be analyzing results over longer time frames (hours) compared to the image capture time (six seconds), take snapshot clusters. By example, take a series of 10 - 100 six second images each hour. Average those images to lower the contributions from stray artifacts (e.g. airplanes that fly in and out of the view frame when the camera captures the image) and to average out certain aspects of the image noise.

You will want to test one image of a six second shot to confirm that it captures both the lowest and highest intensity of light you need. When the lowest light you must have is not captured at all, you will need to increase exposure time or go to a faster lens. When the highest light you expect saturates the image, you will need either to lower exposure time or add a neutral filter (and of course repeat all of the single-shot low light tests).

You will want the image to be in focus. Set the focus during the day and hold it for the night shots. Also, use the day shots to define the "region of interest" precisely in the image analysis software.

Finally, learn what is meant by image processing. At a base level, without even thinking about the hardware, you will have to appreciate red, green, blue channels and how they are combined to gray. Then, you will have to appreciate how the camera sees RGB. A recommendation at this point is to spend time browsing sites devoted to image analysis for science/engineering. This includes sites for programs such as ImageJ (free) or higher end commercial programs such as Igor Pro. Those forums have users who have tackled the issues of proper camera setup for analogous systems as yours and proper post-analysis to obtain results that are not only consistent but also accurate.