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Analog vs Digital Analog Continuous value at continuous locations Used in differential-integral math Digital Continuous/discrete value at discrete locations Used in linear algebra math I(x, y) at (x, y) I(m, n) at (m, n), m = [1, M], n = [1, N]
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Image Representation
Last update 2015. 1st MarchHeejune Ahn, SeoulTech
1. Image Digital Image
Pixels, 2-Dimensional function of sensor value Origin: top-left, not bottom-left m (row index, vertical, i.e., y), n (col. Index,
horizontal, ie. x) 3-D image
voxels E.g. medical, 3D scanning
I(m, n) at (m, n), m = [1, M], n = [1, N]
I(0,n)
I(m,0) I(m,n)
Analog vs Digital Analog
Continuous value at continuous locations Used in differential-integral math
Digital
Continuous/discrete value at discrete locations Used in linear algebra math
I(x, y) at (x, y)
I(m, n) at (m, n), m = [1, M], n = [1, N]
2. Image values # of values/channels :1 to many Single value
gray scale Color map
Gray map : [0, max] to [black to white] False color map : [0. max] to “many colors”
Medical, astronomical application Better recognition (HVS: limited only 40 contrast
levels) E.g.) Jet-color map
3 channels (R,G,B), (H,S,V)
[0, max]
Color-map Color display (R, G, B)
2. Resolution Accuracy of data Spatial resolution: # of pixels, e.g. MxN in 2D Temporal resolution: fps (frame/sec) Bit resolution (dynamic range): 1 bit, 8 bits,
24 bits, floating points.
Real image resolution Representation vs real resolution How to determine image’s resolution Useful for real-time implementation &
performance
3. Image file format Image file
File header + image values
Types file type, resolution, compression, etc
Image data types Binary image: value = {0, 1}
0: black, background, 1: white, foreground Often mapped into [0, 255] E.g. Fax, resultant image
Gray-scale (intensity): [0,255] R,G,B true color: I[m,n, channel] channel=1,2,3 Floating point types
scientific & medical image, e.g. TIFF, medical DICOM
4. Color spaces RGB
[min, max] to [0, 1] RGB to gray-scale
IGRAY(n,m) = IR(n,m) + IG(n,m) + IB(n,m)
IGRAY(n,m)=0.2989IR(n,m)+0.5870IG(n,m)+0.1140 IB(n,m) Gray to RGB is impossible (irreversible)
HSV perceived luminance physical power
HSV (perceptual color space) H (hue) : dominant wavelength S (saturation) : the purity of color V (value) : brightness/luminance Less sensitive to lighting condition than RGB In Matlab : (0, 1)
5. Image in Matlab “im” prefix
image toolbox function starts with it. Read, write, & Query image files
iminfo, imwrite, imread Basic display
imshow: image data (value range [0,255]) imagesc: auto scaling/color map(any matrix input)
accessing pixel value imview
Converting types rgb2gray, rgb2hsv, hsv2rgb