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2.5. VALUESMANIPULATION
91
Example126:image.jpg --apply
curve 1,0,0,128,255,255,0
2.5.2 -apply
gamma
Arguments:
• gamma>=0
Apply gamma correction to selected images.
Example 127 : image.jpg --apply
gamma 2
2.5.3 -balance
gamma
Arguments:
ref
color1,...
Compute gamma-corrected color balance of selected image, with respect to specified reference color.
Default value:
• ’ref
color1=128’.
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92
CHAPTER 2. LIST OF COMMANDS
Example 128 : image.jpg --balance
gamma 128,64,64
2.5.4 -complex2polar
Compute complex to polar transforms of selected images.
Example 129 : image.jpg --fft -complex2polar[-2,-1] -log..
-shift..
50%,50%,0,0,2 -remove.
2.5.5 -compress
clut
Arguments:
max
nbpoints>=1,
max
error>=0,
avg
error>=0
Compress selected color LUTs as sequences of colored keypoints.
Default values:
• ’max
nb
points=2048’, ’max
error=17.5’ and ’avg
error=1.75’.
2.5.6 -compress
rle
Arguments:
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2.5. VALUES MANIPULATION
93
is
binary
data={ 0
| 1 },
maximum
sequence
length>=0
Compress selected images as 2xN data matrices, using RLE algorithm.
Set ’maximum
sequence
length=0’ to disable maximum length constraint.
Default values:
• ’is
binary
data=0’ and ’maximum
sequence
length=0’.
Example 130 : image.jpg -resize2dy 100 -quantize 4 -round --compress
rle , --decompress
rle.
2.5.7 -cumulate (+)
Arguments:
• { x
| y
| z
| c }..{ x
| y
| z
| c }
• (no arg)
Compute the cumulative function of specified image data, optionally along the specified axes.
Example 131 : image.jpg --histogram --cumulate.
-display
graph[-2,-1] 400,300,3
2.5.8 -cut (+)
Arguments:
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CHAPTER 2. LIST OF COMMANDS
• { value0[%]
| [image0] },{ value1[%]
| [image1] }
• [image]
• (no arg)
Cut values of selected images in specified range.
(eq. to
’-c’
).
(no arg) runs interactive mode (uses the instant display window [0] if opened).
In this case, the chosen cut values are returned in the status.
Example 132 : image.jpg --add 30% -cut.
0,255
Example 133 : image.jpg --cut 25%,75%
2.5.9 -decompress
clut
Arguments:
width>0,
height>0,
depth>0
Decompress color LUT expressed as a list of colored keypoints.
Default value:
• ’width=height=depth=64’.
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2.5. VALUES MANIPULATION
95
2.5.10 -decompress
rle
Decompress selected 2xN data matrices, using RLE algorithm.
2.5.11 -discard (+)
Arguments:
value1,
value2,...
• { x
| y
| z
| c}..{ x
| y
| z
| c},
value1,
value2,...
• (no args)
Discard specified values in selected images or discard neighboring duplicate values, optionally only for the
values along the first of a specified axis.
If no values are specified, neighboring duplicate values are discarded.
If all pixels of a selected image are discarded, an empty image is returned.
Example 134 : (1;2;3;4;3;2;1) --discard 2
Example 135 : (1,2,2,3,3,3,4,4,4,4) --discard x
2.5.12 -eigen2tensor
Recompose selected pairs of eigenvalues/eigenvectors as 2x2 or 3x3 tensor fields.
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96
CHAPTER 2. LIST OF COMMANDS
Tutorial page:
http://gmic.eu/tutorial/_eigen2tensor.shtml
2.5.13 -endian (+)
Arguments:
datatype
Reverse data endianness of selected images, eventually considering the pixel being of the specified datatype.
’datatype’ can be { uchar | char | ushort | short | uint | int | uint64 | int64 | float | double }.
2.5.14 -equalize (+)
Arguments:
nb
levels>0[%],
value
min[%],
value
max[%]
Equalize histograms of selected images.
If value range is specified, the equalization is done only for pixels in the specified value range.
Default values:
• ’nb
levels=256’, ’value
min=0%’ and’value
max=100%’.
Example 136 : image.jpg --equalize
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2.5. VALUES MANIPULATION
97
Example 137 : image.jpg --equalize 4,0,128
2.5.15 -fill (+)
Arguments:
• value1,
value2,..
• [image]
• ’formula’
Fill selected images with values read from thespecified value list, existing imageor mathematical expression.
Single quotes may be omitted in ’formula’.
(eq. to
’-f’
).
Example 138 : 4,4 -fill 1,2,3,4,5,6,7
98
CHAPTER 2. LIST OF COMMANDS
Example 139 : 4,4 (1,2,3,4,5,6,7) -fill..
[-1]
Example 140 : 400,400,1,3 -fill "X=x-w/2; Y=y-h/2; R=sqrt(Xˆ2+Yˆ2); a=atan2(Y,X);
if(R<=180,255
*
abs(cos(c+200
*
(x/w-0.5)
*
(y/h-0.5))),850
*
(a%(0.1
*
(c+1))))"
2.5.16 -float2int8
Convert selected float-valued images to 8bits integer representations.
2.5.17 -int82float
Convert selected 8bits integer representations to float-valued images.
2.5.18 -index (+)
Arguments:
• { [palette]
| predefined
palette },0<=
dithering<=1,
map
palette={ 0
| 1 }
Index selected vector-valued images by specified vector-valued palette.
’predefined
palette’ can be { 0=default | 1=HSV | 2=lines | 3=hot | 4=cool | 5=jet | 6=flag | 7=cube
}.
2.5. VALUES MANIPULATION
99
Default values:
• ’dithering=0’ and ’map
palette=0’.
Example 141 : image.jpg --index 1,1,1
Example 142 : image.jpg (0;255;255ˆ0;128;255ˆ0;0;255) --index..
[-1],1,1
Tutorial page:
http://gmic.eu/tutorial/_index.shtml
2.5.19 -inrange
Arguments:
• min[%],max[%]
Detect pixels whose values are in specified range [min,max], in selected images.
(eq. to
’-ir’
).
100
CHAPTER 2. LIST OF COMMANDS
Example 143 : image.jpg --inrange 25%,75%
2.5.20 -map (+)
Arguments:
• [palette],
boundary
• predefined
palette,
boundary
Map specified vector-valued palette to selected indexed scalar images.
’predefined
palette’ can be { 0=default | 1=HSV | 2=lines | 3=hot | 4=cool | 5=jet | 6=flag | 7=cube
}.
’boundary’ can be { 0=dirichlet | 1=neumann | 2=periodic }.
Default value:
• ’boundary=0’.
Example 144 : image.jpg --luminance -map.
3
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