Image enhancement

1
Digital image processing

Chapter 6. Image enhancement
IMAGE ENHANCEMENT Introduction Image
enhancement algorithms techniques
Point-wise operations Contrast
enhancement contrast stretching
Grey scale clipping image binarization
(thresholding) Image inversion
(negative) Grey scale slicing
Bit extraction Contrast
compression Image subtraction
Histogram modeling histogram
equalization/ modification Spatial
operations Spatial low-pass
filtering Unsharp masking and
crispening Spatial high-pass and
band-pass filtering Inverse contrast
ratio mapping and statistical scaling
Magnification and interpolation (image zooming)

2
Digital image processing

Chapter 6. Image enhancement
Transform domain image processing
Generalized linear filtering Non-linear
filtering Generalized cepstrum and
homomorphic filtering Image pseudo-coloring
Color image enhancement Applications
biomedical image enhancement Types and
characteristics of biomedical images Contour
detection in biomedical images Anatomic
segmentation of biomedical images Histogram
equalization and pseudo-coloring in biomedical
images  
3
Digital image processing

Chapter 6. Image enhancement

• Introduction
• Def. Image enhancement class of image
  processing operations whose goal is to produce an
  output digital image that is visually more
  suitable as appearance for its visual examination
  by a human observer
• The relevant features for the examination task
  are enhanced
• The irrelevant features for the examination task
  are removed/reduced
• Specific to image enhancement
• - input digital image (grey scale or color)
• - output digital image (grey scale or color)
• Examples of image enhancement operations
• noise removal
• geometric distortion correction
• edge enhancement
• contrast enhancement
• image zooming
• image subtraction
• pseudo-coloring.

4
Digital image processing

Chapter 6. Image enhancement
A. Point-wise operations Def. The new grey
level (color) value in a spatial location (m,n)
in the resulting image depends only on the grey
level (color) in the same spatial location (m,n)
in the original image gt point-wise
operation, or grey scale transformation (for grey
scale images).

5
Digital image processing

Chapter 6. Image enhancement
Contrast enhancement/contrast stretching

Contrast enhancement, if
? mlt1, for the dark
regions (under a?L/3). ? ngt1, for the
medium grey scale (between a and b, b?(2/3)L)
? plt1, for the bright regions (above b).
6
Digital image processing

Chapter 6. Image enhancement

• Grey scale clipping image thresholding
• Grey scale clipping is a particular case of
  contrast enhancement, for mp0
  
• (6.2)

Fig.
6.3. Grey scale clipping

Fig. 6.4 Image thresholding
7
(No Transcript)
8
Digital image processing

Chapter 6. Image enhancement
  Fig. 6.5 Image thresholding -
example   The inverse image (negative
image) v L-u
(6.3)
Fig. 6.6 Image
inverting
Fig. 6.7 Grey scale slicing (windowing)
9
Digital image processing

Chapter 6. Image enhancement
GREY SCALE SLICING (WINDOWING)  

(6.4) or
(6.5) BIT
EXTRACTION
uk12B-1k22B-2...kB-12kB
(6.6)  
(6.7) CONTRAST COMPRESSION
v clog(1u)
(6.8)
10
CONTRAST COMPRESSION EXAMPLE v
clog(1u)
11
IMAGE SUBTRACTION
_
12
Digital image processing

Chapter 6. Image enhancement
13
Digital image processing

Chapter 6. Image enhancement
Fig. 6.8. Histogram equalization



a

b Fig. 6.9 Low contrast image

a

b Fig. 6.10 The resulting image
after histogram equalization
14
Digital image processing

Chapter 6. Image enhancement
Fig.
6.11 Histogram modification  


15
Digital image processing

Chapter 6. Image enhancement
SPATIAL OPERATIONS most of them can be
implemented by convolution  

16
Digital image processing

Chapter 6. Image enhancement
Spatial averaging. Low-pass spatial
filtering  
(6.18)
(6.19)
v(m,n)1/2y(m,n)1/4y(m-1,n)y(m1,
n)y(m,n-1)y(m,n1)
(6.20)    
Fig. 6.12 Convolution windows used in low-pass
spatial filtering - examples
Filtering by spatial averaging the effect on
the noise power reduction 
(6.21)  

(6.22)
17
Digital image processing

Chapter 6. Image enhancement
Directional low-pass spatial filtering

(6.23)    
Fig. 6.13
Directional spatial filtering  
Median filtering (6.24) ? v(m,n)
the element in the middle of the brightness
row, with increasing brightness values
   
18
Digital image processing

Chapter 6. Image enhancement
(6.25)
(6.26)
a
b
c
d
Fig. 6.16
Edge crispening algorithm
19
Digital image processing

Chapter 6. Image enhancement



Original image
Resulting image Fig. 6.17 Edge crispening using a
Laplacian operator   HIGH-PASS SPATIAL
FILTERING (6.27)  
 
 
Fig. 6.18 Low-pass filtering
Fig. 6.19 High-pass filtering  
 
20
Digital image processing

Chapter 6. Image enhancement
BAND-PASS SPATIAL FILTERING
(6.28)

Fig. 6.20 Band-pass image filtering
21
Digital image processing

Chapter 6. Image enhancement

•  
• MAGNIFICATION AND INTERPOLATION (IMAGE ZOOMING)
• Zooming by pixel replication
• (6.34)
•  
• The resulting image is obtained as 
• (6.35)
•  
• with m,n 0, 1,
  2,...

22
Digital image processing

Chapter 6. Image enhancement

a b
c
Fig. 6.22 Image zooming by pixel
replication by a factor of b) 2 c) 4, on each
direction Zooming by linear interpolation
(6.36)  
(6.37)  
(6.38)  
(6.39)    
(6.40)  
   




Fig. 6.23
23
Digital image processing

Chapter 6. Image enhancement

• 6.6 TRANSFORM DOMAIN IMAGE PROCESSING
•  
•  
•  
• Generalized linear filtering
•  
• (6.41)
•   where g(k,l) is called regional mask (i.e., it
  is 0 outside the selected region)

Fig. 6.24 Image enhancement in the
transformed domain
a
b
Fig. 6.25 Regional masks for the
generalized linear filtering
24
Digital image processing

Chapter 6. Image enhancement
E.g. - the inverse Gaussian filter has the
following regional mask
  (6.42)   - for other
orthogonal transforms
(6.43)     Non-linear filtering  
(6.44)    
(6.45)
Generalized cepstrum and homomorphic
filtering   
   
25
Digital image processing

Chapter 6. Image enhancement
IMAGE PSEUDO-COLORING  
Fig. 6.27 Monochrome
image pseudo-coloring
COLOR IMAGE ENHANCEMENT    
Fig. 6.28 Color
image enhancement block diagram
26
Digital image processing

Chapter 6. Image enhancement
BIOMEDICAL IMAGE ENHANCEMENT -
APPLICATIONS   Biomedical image types
features    
Fig. 6.42

Fig. 6.43  
Fig.
6.44 Fig. 6.45

27
Digital image processing

Chapter 6. Image enhancement
Contour extraction in biomedical
images Table 6.1    
(6.76)            

Fig. 6.46
Fig. 6.47
28
Digital image processing

Chapter 6. Image enhancement
Histogram equalization and pseudo-coloring in
biomedical images  

a
b
Fig. 6.48  
Fig. 6.49
Fig. 6.50
29
Digital image processing

Chapter 6. Image enhancement
   
Fig. 6.51

Fig. 6.52           
Fig. 6.53
Fig. 6.54