CIS 558 / Linguistics 525
Computer Analysis and Modeling of Biological Signals and Systems
Homework 2
Due: 2/5/2014
Color Matching
The background for this homework is the lecture on early
color vision.
Download colmatch.mat to a place where Octave can find it, and load it with the command
load("colmatch.mat");
This file contains a number of matrices and vectors related to the color matching
problems discussed in class. In particular, the variable P
is an N x 3 matrix containing wavelength spectra for three basis lights
("primaries''), and the variable M is
a 3 x N color-matching matrix corresponding to these primaries. For these
problems N=31, corresponding to samples of the wavelength spectrum from
400nm to 700nm in increments of 10nm.
You'll remember that a "color-matching matrix" maps a test light onto the weights of basis lights that match it. In the lecture notes, we used the equation e = Ct, where t is an N x 1 column vector (the "test light"), C is a 3 x N matrix (the "color-matching matrix"), and e is a 3 x 1 column vector (the weighting of the primary lights that match the test light). Essentially we are projecting an N-dimensional space (here 31-dimensional) into a 3-dimensional linear subspace.
Set the variable light
to a random vector of length 31 (help rand
will give you information about how to do this). We will consider this vector to represent the 31-dimensional wavelength spectrum of a test light.
- What combination of the three primaries in P
will match the appearance of this randomly chosen test light? Compute the
wavelength spectrum of the matching light (as a linear combination of the
three primary wavelength spectra) and compare it to that of the test light.
Why is it different?
- The variable Palt
contains a different set of primary lights. Compute the corresponding
matching matrix Malt (you will
probably need to make use of the Matlab function inv
which computes the inverse of a square matrix, and look again at the section of the lecture notes under the heading New color-matching matrices from old). Repeat the previous exercise
with Palt and Malt.
Is the matching spectrum different than in the previous exercise?
- The variable Phosphors contains
the emission spectra of three standard color monitor phosphors. How would
you choose the amplitude of each phosphor's emission in order to produce light
on the monitor that matches light?
Compute these amplitudes and demonstrate that the resulting mixture of phosphors
does indeed produce the same tri-stimulus coordinates in the matching experiment.
- The variable M2 contains yet
another matching matrix. This one was computed for a color-impaired individual,
using the primaries in P. Compute the SVD of M2.
How can you tell this individual is color-impaired? Assume that the individual
has a standard color-blindness problem: they are missing one or more cone
types. Derive the spectral sensitivity of the missing (or remaining) cone.
- The variable Cones contains
approximate spectral sensitivities of t he three color photoreceptors (cones)
in the human eye. They are ordered such that Cones(1,:)
corresponds to the L (long-wavelength, or red) cones, Cones(2,:)
the M (green) cones, and Cones(3,:)
the S (blue) cones. Plot these using plot
or try rgbplot, and compare to the cone
sensitivity vector you derived in the previous problem. Which cone was missing
from (or remaining in) your color-blind subject?
- Having just purchased a new house in Center City, you decide to paint the
baseboard trim a new color. In particular, you'd like to have the trim match
the color of your new couch (chartreuse, of course). You make a trip to the
paint store, carrying with you a sample piece of fabric (complete with plastic
slipcover). The store carries two brands of paint: ShabbyTint,
which is mixed from three primary colors, and RichTone,
which is mixed from a set of six primary colors. Naturally, the RichTone
costs four times as much, so you decide to go with the ShabbyTint,
and quickly pick a matching color from the ShabbyTint
paint chart (the store mixes it for you, from the three ShabbyTint
primaries).
Load the file paint.mat into Matlab.
This will define a few variables:
- couch contains a vector
of the color reflectance function of the couch.
- shabby is a matrix whose
columns are the reflectance functions of the three ShabbyTint
primaries.
- rich is a matrix whose
columns are the reflectance functions of the six RichTone primaries.
- fluo contains a vector
of the color spectrum of the fluorescent lights in the paint store, and
in your living room.
- daylight contains a vector
of color spectrum of the sun.
- Determine the mixture of ShabbyTint
primaries that will match the sample you've taken to the paint store.
Assume that paint-mixing is additive (it really isn't!). Plot the wavelength
spectra of the sample and the paint (when viewed in the paint store) on
the same plot (use the Matlab hold
command to do this). Demonstrate that a paint mixed from this proportion
of the three primaries will look just like the sample.
- You may now view these colors on your monitor. To do this, first download
the MATLAB m-file showcols.m and place it where
MATLAB (or Octave) can "see" it. Then create two column vectors
of height 3, called rgb1
and rgb2 containing the
monitor gun values (proportion of each phosphor) to be used to display
a color matching the couch and the shabby paint mixture under fluorescent
lighting. You should assume that the matrix Phosphors
contains emission spectra that are correct for your monitor (this may
not be true). Then call the function
showcols(rgb1,rgb2)
.
- You take the paint home, and paint a small sample of baseboard. The
next morning, when the sun comes up, you find to your horror that the
baseboard doesn't match the couch at all. What happened? Show that the
two colors really don't match when viewed under daylight. Render
them on the screen using
showcols
to check this.
- What is the best (least-squares) combination of ShabbyTint
primaries that you could have used to match the couch both in daylight
and fluorescent light?
- What if you use the RichTone paint?
Assess the quality of the best-matching mixture under both daylight and
fluorescent light.