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2.5. VALUESMANIPULATION
101
Example145:image.jpg --rgb2ycbcr r -split.
c (0,255,0) -resize.
256,1,1,1,3 -map[-4] [-1]
-remove.
-append[-3--1] c -ycbcr2rgb.
Tutorial page:
http://gmic.eu/tutorial/_map.shtml
2.5.21 -map
clut
Arguments:
• [clut]
Map specified RGB color LUT to selected images.
Example 146 : image.jpg -uniform
distribution {2ˆ6},3 -mirror.
x --map
clut[0] [1]
2.5.22 -mix
channels
Arguments:
• (a00,...,aMN)
Apply specified matrix to channels of selected images.
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102
CHAPTER 2. LIST OF COMMANDS
Example 147 : image.jpg --mix
channels (0,1,0;1,0,0;0,0,1)
2.5.23 -negative
Compute negative of selected images.
Example 148 : image.jpg --negative
2.5.24 -noise (+)
Arguments:
• std
variation>=0[%],
noise
type
Add random noise to selected images.
’noise
type’ can be { 0=gaussian | 1=uniform | 2=salt&pepper | 3=poisson | 4=rice }.
Default value:
• ’noise
type=0’.
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2.5. VALUES MANIPULATION
103
Example 149 : image.jpg --noise[0] 50,0 --noise[0] 50,1 --noise[0] 10,2 -cut 0,255
Example 150 : 300,300,1,3 [0] -noise[0] 20,0 -noise[1] 20,1 --histogram 100
-display
graph[-2,-1] 400,300,3
2.5.25 -normlp
Arguments:
• p>=0
Compute the pointwise Lp-norm norm of vector-valued pixels in selected images.
Default value:
• ’p=2’.
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104
CHAPTER 2. LIST OF COMMANDS
Example 151 : image.jpg --normlp[0] 0 --normlp[0] 1 --normlp[0] 2 --normlp[0] inf
2.5.26 -norm
Compute the pointwise euclidean norm of vector-valued pixels in selected images.
Example 152 : image.jpg --norm
Tutorial page:
http://gmic.eu/tutorial/_norm.shtml
2.5.27 -normalize (+)
Arguments:
• { value0[%]
| [image0] },{ value1[%]
| [image1] }
• [image]
Linearly normalize values of selected images in specified range.
(eq. to
’-n’
).
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2.5. VALUES MANIPULATION
105
Example 153: image.jpg -split x,2 -normalize.
64,196 -append x
Tutorial page:
http://gmic.eu/tutorial/_normalize.shtml
2.5.28 -normalize
sum
Normalize selected images with a unitary sum.
Example 154 : image.jpg --histogram.
-normalize
sum.
-display
graph.
400,300
2.5.29 -not
Apply boolean not operation on selected images.
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106
CHAPTER 2. LIST OF COMMANDS
Example 155 : image.jpg --ge 50% --not.
2.5.30 -orientation
Compute the pointwise orientation of vector-valued pixels in selected images.
Example 156 : image.jpg --orientation --norm..
-negative.
-mul..
[-1] -reverse[-2,-1]
Tutorial page:
http://gmic.eu/tutorial/_orientation.shtml
2.5.31 -oneminus
For each selected image, compute one minus image.
2.5. VALUES MANIPULATION
107
Example 157 : image.jpg -n 0,1 --oneminus
2.5.32 -otsu
Arguments:
nb
levels>0
Hard-threshold selected images using Otsu’s method.
The computed thresholds are returned as a list of values in the status.
Default value:
• ’nb
levels=256’.
Example 158 : image.jpg -luminance --otsu ,
2.5.33 -polar2complex
Compute polar to complex transforms of selected images.
2.5.34 -quantize
Arguments:
• nb
levels>=1,
keep
values={ 0
| 1 },
is
uniform={ 0
| 1 }
Quantize selected images.
Default value:
• ’keep
values=1’ and ’is
uniform=0’.
108
CHAPTER 2. LIST OF COMMANDS
Example 159 : image.jpg -luminance --quantize 3
Example 160 : 200,200,1,1,’cos(x/10)
*
sin(y/10)’ --quantize[0] 6 --quantize[0] 4 --quantize[0]
3 --quantize[0] 2
2.5.35 -rand (+)
Arguments:
• { value0[%]
| [image0] },
{ value1[%]
| [image1] }
• [image]
Fill selected images with random values uniformly distributed in the specified range.
2.5. VALUES MANIPULATION
109
Example 161 : 400,400,1,3 -rand -10,10 --blur 10 -sign.
2.5.36 -replace
Arguments:
• value
src,value
dest
Replace pixel values in selected images.
Example 162 : (1;2;3;4) --replace 2,3
2.5.37 -replace
inf
Arguments:
expression
Replace all infinite values in selected images by specified expression.
110
CHAPTER 2. LIST OF COMMANDS
Example 163 : (0;1;2) -log --replace
inf 2
2.5.38 -replace
nan
Arguments:
expression
Replace all NaN values in selected images by specified expression.
Example 164 : (-1;0;2) -sqrt --replace
nan 2
2.5.39 -replace
seq
Arguments:
• "search
seq","replace
seq"
Search and replace a sequence of values in selected images.
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