IPCV ‘06 August 21 – September 1 Budapest Jussi Parkkinen Markku Hauta-Kasari Department of...
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Transcript of IPCV ‘06 August 21 – September 1 Budapest Jussi Parkkinen Markku Hauta-Kasari Department of...
IPCV ‘06August 21 – September 1
Budapest
Jussi ParkkinenMarkku Hauta-Kasari
Department of Computer ScienceUniversity of Joensuu, Finland
http://spectral.joensuu.fi/
Introduction to spectral color
COLOR ANALYSIS
Eriväristen lehtien spektrejä
Spectral images from real and artificial indoor plants Kanae Miyazawa
Display characterictics
Principle of color detection
Light source
Colored object
Detection system•biological•artificial
Color image formation in human eye
CIE Illum inations D65, A and C
0
50
100
150
200
250
300
300 350 400 450 500 550 600 650 700 750 800
Wavelength (nm)
D65
A
C
RGB vs. Spectrum
• Is the spectrum needed?
• RGB is just a 3D projection of a spectrum
• RGB can produce nice colors on display, but not correct colors
Spectral approach to color
• In spectral approach, color is represented by color signal. This causes the color sensation
• The signal is part of electromagnetic spectrum
- in human color vision the range is 380-780 nm
• In spectral approach, we are not limited into this human visual range
What should be the spectralresolution, i.e.
the sampling rate in wavelenths?
Spectral dependence on sampling
Color dependence on sampling
Change of RGB-values due to sampling
Can we reproduce a spectrum from the RGB-values?
Data• 1494 color samples in 200 color images
– Munsell colors, Color checker, natural colors, wall paint
– cameras: Fuji FinePix and Canon Powershot
– illuminants: A and D65
Methods
1. Polynomial model (R, G, B, R2, G2, B2, ..)
2. Kernel models
Evaluation
• delta E and RMSE (for spectra)– average, std, maximum
Spectra with largest delta E polynomial model
Some preliminary tests with mobile phones cameras
Some preliminary tests with mobile phones cameras
Spektrikuvan kanavakuvia
Spectral Face Image
Spectral Image
Image Types
TYPE SPECTRAL CHANNELS---------------------------------------• Gray-scale• Trichromatic• Spectral
– Hyperspectral• Real-time spectral
• Single• Three• >3• Numerous• Numerous
MEMORY REQUIREMENTS OF IMAGES
Image size 256x256 512x512
gray-level image 65 kB 262 kB
color (RGB-) image 196 kB 786 kB
spectral, 20 nm resol. 1 MB 4 MB
spectral, 5 nm resol. 3 MB 15 MB
Pixels in color image are vectors
• What is the order of color?
• What means the average color?
• How to compute distance in spectral space?
• What is the structure of spectral color space?
Statistical Analysis of Natural Images
Statistical Analysis of Natural Images
Munsell system for color representation
Spectrum and Hue, Saturation, and Value
(a) (b) (c)
400 500 600 7000
20
40
60
80
100
Wavelength(nm)
Reflec
tance
(%)
400 500 600 7000
20
40
60
80
100
Wavelength(nm)
Reflec
tance
(%)
400 500 600 7000
20
40
60
80
100
Wavelength(nm)
Reflec
tance
(%)
Motivation for spectral color
• Not to loose important color information
• To define optimal color sensors
• To develop better color vision models
• To develop novel instruments
• To develop spectral color classifiers and optical implementations for them
What is color?
”Color is more than light” ”Computer cannot describe color correctly”
”Color is a perception (of human beings)”• => Color cannot been measured!• => Is this fair to animals?
• In spectral approach, color is represented by color signal. This causes the color sensation
• In spectral approach, we are not limited into this human visual range