Transcript

Metamerism? What metamerism?

Lewis D Griffin

Computer Science,

University College London

http://www.onlandscape.co.uk/2012/02/the-myth-of-universal-colour/#/

Metamerism in Colour Vision

artificial illuminant

natural illuminant

cone sensitivity functions

The cone response triple is the same for both illuminants.

9.1

8.8

7.2

2.1

-1.2 0.7

2.1 -0.6 1.4

-3.2 -2.8 0.1 2.2

-3.4 0.1 -0.2 0.8 4.5

=.

Metamerism in local Spatial Vision

a jetDerivatives-of-Gaussians area good model of V1 simple cells

Why is Metamerism a problem?

2.1

-1.2 0.7

2.1 -0.6 1.4

-3.2 -2.8 0.1 2.2

-3.4 0.1 -0.2 0.8 4.5

=

Non-linear feature classifier circuitry

edge bar T-junction……

.

Q: How should this work, given this?

Metamery Class

J2,3 J7 J12,2,7……symmetry groups

Need to decide when jets are similar.

Jet similarity should conform to the linearity of the measurement process.

Therefore what is needed is an Inner Product structure.

The Beezer 1962

2.4

0.7

2.1

1.3

Inner Product

6.3

0 0

T

1 1 0 0 1 1 2 2

2 2

1 0 0

, : 0 1 0

0 0 1

j k

j k j k j k j k j k j k

j k

There is an infinity of possible Inner Products on jets…

The dot product

Gram Matrix based

3

T 3

3 5

9 0 6

, 0 30 0

6 0 12

j k j k

The scale-space Inner Product

T 2

4

2 0 0

, 0 2 0

0 0

j k j k …but this one is best

A Jet Space IP induces an Image IP

T

1 0 0 0

0 1 0 0

0 0 1 0

0 0 0 1

j k

T

A way to measure how similar jets are, is equivalent to a rule to measure how similar images are

Dot product Gram Matrix Scale-Space

Image IPs can also be expressed in the Frequency Domain

T

T

Dot product

spatialdomain

frequencydomain

Gram Matrix Scale-Space

measure imageswith filters to make jets

4 62

0 0 1 1 2 2 3 32 6,j k j k j k j k j k

compare jets using the ‘scale space’ inner product

compare images using this fourier inner product

then =

filter imagesthen

window images compare images using this fourier inner product

=thencompare them

using a standard inner product

How good is the approximation?

• 1.0% error for images with flat spectra

• 0.1% error for ‘natural’ images with 1/f spectra.

fuzzy window

frosted glass

Approximately equal ‘views from the inside’

Simple cell assembly

2.1

-1.2 0.7

2.1 -0.6 1.4

-3.2 -2.8 0.1 2.2

-3.4 0.1 -0.2 0.8 4.5

=.

Non-linear feature classifier circuitry

edge bar T-junction……J2,3 J7 J12,2,7……symmetry groups

Filtering has no effect on symmetries!

+2+2 +1

+1

+1

+1

Metamerism? What metamerism?

Thank you for your attention

fuzzy window

frosted glass

Approximately equal ‘views from the inside’

Simple cell assembly

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