Recreating Spectral Response from 6-Channel Color Sensor

  • I
  • Thread starter AxisCat
  • Start date
  • #1
AxisCat
40
4
Hi All,

This is a project I started a couple of years ago then got stuck or bored and stopped working on it. I am thinking about picking back up where I left off. I am using a AMS AS7262 color sensor with the following overlapping channels: 450, 500, 550, 570, 600 and 650 nm, each with 40nm FWHM.

I used a Digikröm CM110 Monochromator and stepped through the spectrum in 1nm increments saving the output from the sensor to a file. My light source was a standard 100 watt halogen household bulb. This is what I measured:
chart.jpg

The continuous dark blue curve is from a photodiode I am trying to use as a reference. I understand this is really hard stuff to do with the limited equipment I have available. Is it even possible to recreate a fairly accurate spectral response using just these 6 discrete channels? The manufacturer provides some information that eludes to it being possible.

Anyone have any thoughts?

Thanks,
Axis
 
Science news on Phys.org
  • #2
AxisCat said:
Hi All,

This is a project I started a couple of years ago then got stuck or bored and stopped working on it. I am thinking about picking back up where I left off. I am using a AMS AS7262 color sensor with the following overlapping channels: 450, 500, 550, 570, 600 and 650 nm, each with 40nm FWHM.

I used a Digikröm CM110 Monochromator and stepped through the spectrum in 1nm increments saving the output from the sensor to a file. My light source was a standard 100 watt halogen household bulb. This is what I measured:
View attachment 336147
The continuous dark blue curve is from a photodiode I am trying to use as a reference. I understand this is really hard stuff to do with the limited equipment I have available. Is it even possible to recreate a fairly accurate spectral response using just these 6 discrete channels? The manufacturer provides some information that eludes to it being possible.

Anyone have any thoughts?

Thanks,
Axis

Off the top of my head, I suggest that you first normalize each channel and then assign/compute wavelengths according to ratios of the different channels- that's generally how color vision works.
 
  • #3
I appreciate the reply. The "mapping function" is the part I am stuck on. Someone suggested Fourier transforms because the curves looked like filters and the math can be reversed. That looked really complicated so I haven't researched it any further. Another person's thought was using a matrix to calibrate. The input matrix would be 6x1 (sensor output x 6-channels), the correction matrix would be 6x300 (700nm - 400nm), and the output matrix would be a 1x300 representing the spectral response from 400-700nm. I really don't know which direction to take with this.
 

1. What is a 6-channel color sensor?

A 6-channel color sensor is a type of sensor that measures the intensity of light across six different color channels: red, green, blue, cyan, magenta, and yellow. This allows for a more accurate and comprehensive measurement of color compared to traditional RGB sensors.

2. How does a 6-channel color sensor work?

A 6-channel color sensor works by using a combination of filters and photodiodes to detect and measure the intensity of light in each color channel. The output from each channel is then combined to recreate the spectral response of the light source being measured.

3. What is spectral response?

Spectral response refers to the sensitivity of a sensor to different wavelengths of light. In the context of a 6-channel color sensor, it is the measurement of the intensity of light across the six color channels.

4. Why is it important to recreate spectral response from a 6-channel color sensor?

Recreating spectral response from a 6-channel color sensor allows for a more accurate and precise measurement of color. It can also provide valuable information about the composition and properties of the light source being measured.

5. How is spectral response used in scientific research?

Spectral response is used in a variety of scientific research fields, such as colorimetry, spectroscopy, and remote sensing. It can provide insights into the chemical and physical properties of materials, as well as aid in the development of new technologies and products.

Back
Top