Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!cs.utexas.edu!uunet!datapg!com50!midgard!dal
From: dal@midgard.Midgard.MN.ORG (Dale Schumacher)
Newsgroups: comp.graphics
Subject: Re: Color quantization: flesh tones (really RGB->YIQ)
Summary: RGB -> YIQ conversion matrix
Keywords: color rgb yiq quantization
Message-ID: <1212@midgard.Midgard.MN.ORG>
Date: 18 Sep 89 22:52:18 GMT
References: <6087@pt.cs.cmu.edu> <124742@sun.Eng.Sun.COM>
Reply-To: dal@midgard.Midgard.MN.ORG (Dale Schumacher)
Organization: The Midgard Realm, St Paul MN
Lines: 27

In article <124742@sun.Eng.Sun.COM> falk@sun.Eng.Sun.COM (Ed Falk) writes:
|
|Here's a thought; try converting RGB to the NTSC IYQ coordinates
|and quantize in IYQ space.  I suggest this because NTSC chose
|the Y axis to be biased towards flesh tones and TV pictures transmit
|more power along that axis than along the Q axis (I is intensity).
|
|I'm sorry, but I don't have the transformation matrix from RGB to IYQ handy.
|

I thought Y was the intensity (luminance) component... and the most
bandwidth is used for the luminance, with less for the color components.
Here are the integer [0..255] pixel value formulae that I use:

	Y = (((77 * R) + (150 * G) + (29 * B)) / 256);
	I = (((153 * R) + (-70 * G) + (-82 * B)) / 256);
	Q = (((54 * R) + (-134 * G) + (80 * B)) / 256);

	R = (((256 * Y) + (245 * I) + (159 * Q)) / 256);
	G = (((256 * Y) + (-70 * I) + (-167 * Q)) / 256);
	B = (((256 * Y) + (-283 * I) + (436 * Q)) / 256);

The above forms the heart of a utility I wrote to set the luminance (Y)
of a color image from a monochrome image.  I use this in convolutions,
particularly for edge sharpening, such that I do the convolution only
on the luminance component, then recombine the output with the original
color image.