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Image Enhancement in the Spatial DomainImage Enhancement in the Spatial Domain
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Topics� Definitions and basics
� Some Basic Gray Level Transformations
� Histogram ProcessingHistogram Processing
� Enhancement Using Arithmetic/Logic Operations
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Image Enhancement� The principal objective of enhancement is to process
an image so that the result is more suitable than the original image for a specific application
� Enhancement Categories:� Enhancement Categories:
� spatial domain enhancement: refers to the image plane itself, and approaches in this category are based on direct manipulation of pixels in an image
� Frequency domain enhancement: processing techniques are based on modifying the Fourier transform of an image.
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Spatial Domain Processes� Spatial domain processes are denoted by
g(x,y) = T[ f(x,y) ]
� A neighborhood about a point (x, y) is a square or rectangular sub-image area centered at (x, y)
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Basic Gray Level Transformations (1)
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Basic Gray Level Transformations(2)
� Contrast enhancement
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Contrast Enhancement
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Image negation
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Image negation� A mammography image
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Basic Gray Level Transformations� Gamma correction: Power-law transformations
have the basic form s=crγ
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Gamma Correction
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Original Image
Gamma Correction with c=1, γ=0.6
Gamma Correction with c=1, γ=0.4
Gamma Correction with c=1, γ=0.3
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Original Image
Gamma Correction c=1, γ=3
Gamma Correction c=1, γ=4
Gamma Correction c=1, γ=5
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Piecewise Linear Contrast
Stretching
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Gray Level Slicing
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Gray Level Slicing Example
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Bit-plane Slicing
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Histogram Analysis� The histogram of a digital image with gray levels
in the range [0, L-1] is a discrete function h(rk)=nk, where rk is the kth gray level and nk is the number of pixels in the image having gray the number of pixels in the image having gray level rk.
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Example
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Histogram Equalization� Histogram equalization is mapping each pixel
with level rk in the input image into a corresponding pixel with level sk in the output imageimage
� After equalization the gray levels in the histogram are more uniformly distributed
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Histogram equalization (cont.)� The probability of occurrence of gray level rk in
an image is approximated by pr(rK) = nk/n for k=0,..,L-1
� The converted gray level value is:
for k=0,.., L-1
∑ ∑= =
===k
j
k
j
jjrkk n
nrPrTS
0 0
)()(
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Local Histogram Equalization
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Logical Operations� Logical AND
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Logical Operations� Logical OR
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Arithmetic Operations� Image subtraction
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Motion Detection by Image
Subtraction
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Questions?Questions?