# Thread: Smartphone camera colour filter innovation lets in 3x more light

1. ## Smartphone camera colour filter innovation lets in 3x more light

The new single micron thick filter also provides richer colour information to the camera sensor.
Read more.

2. ## Re: Smartphone camera colour filter innovation lets in 3x more light

25 hues in the sensor? That's going to be interesting, a 5x5 subpixel matrix of different wavelength sensors instead of the old RGB?

3. ## Re: Smartphone camera colour filter innovation lets in 3x more light

this sounds pretty cool! there seems undertones that this could be used in proper digital photography too :-)

4. ## Re: Smartphone camera colour filter innovation lets in 3x more light

Full article available here. Like most non-technical summaries, the linked University of Utah article is so dumbed down that it's missed the entire point of the paper itself and instead introduced nonsense that sounds like something completely different (this silly '25 hues' thing).

What the filter actually does is spatially modulate the incoming light into frequency-dependant patterns. A zero-dimensional analogy would be a prism: a beam of light of unknown colour comes in, and by looknig at the patterns in the spectrum that the prism produces, you can figure out the colour of the incoming light. The one-dimensional extension is a very long prism with a 'sheet' of incoming light, allowing you to analyse the incoming colour of a 'line' of light. The problem comes in extending this to two dimensions; you cannot just stack prisms, as you either end up with the prisms intersecting each other or them being so far apart you image looks like a sparse series of lines rather than a square image. It's also wasteful of sensor space, as each imaging pixel only responds to one wavelength and no others. The 2d diffraction grating used in the paper solves this, by scatting incoming light into known overlapping patterns, so that you are not wasting pixels. Once you have this set of overlapping patterns, you then use a 2D correlation process over the image to extract where the patterns are most and least intense, than thus the distribution of wavelengths over the image. How many 'hues' you have is merely down to how many patterns you calibrate with and thus how many correlation passes you perform.

5. ## Received thanks from:

Millennium (02-11-2015),TheAnimus (02-11-2015)

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