Spectral Feature Extraction - Cornell University

CEE 615: Digital Image Processing 8
W. Philpot, Cornell University
Spectral Differencing (subtraction)
Subtracting gray values from different spectral bands.
k' = a 0 + a 1 k 1 + a 2 k 2
• The vector, a = (a 1 ,a 2 ), defines the direction of changing gray value: a 2 = m a 1
• The coefficients may be defined by choosing
(k 11 , k 21 ) => k min = minimum gray value in the new image, and
(k 12 , k 22 ) => k max = maximum gray value in the new image.
The coefficients are given by:
a 2 = m a 1
where:
m = slope of a line parallel to a
a
1
=
k
max
− k
min
( k − k ) + m( k − k )
12 11 22 21
a 0 = k min – a 1 (k 11 + m k 21 )
k min = a 0 + a 1 k 11 + a 2 k 21
k max = a 0 + a 1 k 12 + a 2 k 22
• Spectral differencing is another partitioning of the measurement space.
• The space is partitioned into plane-parallel regions which are perpendicular to the direction
of the coefficient vector a = (a 1 , a 2 ).
• Color information extraction will be optimized if the coefficient vector, is perpendicular
to the direction of highest correlation.
Band 1 Band 2 Band 2 – Band 1
• Pixels that are bright in the difference image are brighter in band 2.
• Pixels that are dark in the difference image are brighter in band 1.
• Gray indicates little or no color change.