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2.8. FILTERING
191
Example310:image.jpg -luminance --fft t -append[-2,-1] ] c -norm.
-log.
-shift.
50%,50%,0,0,2
Example 311 : image.jpg w2={int(w/2)} h2={int(h/2)} -fft -shift $w2,$h2,0,0,2 -ellipse
$w2,$h2,30,30,0,1,0 -shift -$w2,-$h2,0,0,2 -ifft -remove.
Tutorial page:
http://gmic.eu/tutorial/_fft.shtml
2.8.43 -gradient (+)
Arguments:
• { x
| y
| z }..{ x
| y
| z },
scheme
• (no arg)
Compute the gradient components (first derivatives) of selected images.
(eq. to
’-g’
).
’scheme’ can be { -1=backward | 0=centered | 1=forward | 2=sobel | 3=rotation-invariant (default)
| 4=deriche | 5=vanvliet }.
(no arg) compute all significant 2d/3d components.
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192
CHAPTER 2. LIST OF COMMANDS
Default value:
• ’scheme=3’.
Example 312 : image.jpg -gradient
Tutorial page:
http://gmic.eu/tutorial/_gradient.shtml
2.8.44 -gradient
norm
Compute gradient norm of selected images.
Example 313 : image.jpg --gradient
norm -equalize.
Tutorial page:
http://gmic.eu/tutorial/_gradient_norm.shtml
2.8.45 -gradient
orientation
Arguments:
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2.8. FILTERING
193
dimension={1,2,3}
Compute N-d gradient orientation of selected images.
Default value:
• ’dimension=3’.
Example 314 : image.jpg --gradient
orientation 2
2.8.46 -guided (+)
Arguments:
• [guide],radius[%]>0,regularization>0
• radius[%]>0,regularization>0
Blur selected images by guided image filtering.
If a guide image is provided, it is used to drive the smoothing process.
Aguide image must be of the same xyz-size as the selected images.
This command implements the filtering algorithm described in:
He, Kaiming; Sun, Jian; Tang, Xiaoou, ”Guided ImageFiltering,” Pattern Analysis and Machine Intelligence,
IEEE Transactions on , vol.35, no.6, pp.1397,1409, June 2013
Example 315 : image.jpg [0] --guided 5,400
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194
CHAPTER 2. LIST OF COMMANDS
2.8.47 -haar
Arguments:
• scale>0
Compute the direct haar multiscale wavelet transform of selected images.
Tutorial page:
http://gmic.eu/tutorial/_haar.shtml
2.8.48 -heat
flow
Arguments:
nb
iter>=0,
dt,
keep
sequence={ 0
| 1 }
Apply iterations of the heat flow on selected images.
Default values:
• ’nb
iter=10’, ’dt=30’ and ’keep
sequence=0’.
Example 316 : image.jpg --heat
flow 20
2.8.49 -hessian (+)
Arguments:
• { xx
| xy
| xz
| yy
| yz
| zz }..{ xx
| xy
| xz
| yy
| yz
| zz }
• (no arg)
Compute the hessian components (second derivatives) of selected images.
(no arg) compute all significant components.
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2.8. FILTERING
195
Example 317: image.jpg -hessian
2.8.50 -idct
Arguments:
{ x
| y
| z }..{ x
| y
| z }
• (no arg)
Compute the inverse discrete cosine transform of selected images, optionally along the specified axes only.
Default values:
• (no arg)
Tutorial page:
http://gmic.eu/tutorial/_dct-and-idct.shtml
2.8.51 -iee
Compute gradient-orthogonal-directed 2nd derivative of image(s).
Example 318 : image.jpg -iee
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196
CHAPTER 2. LIST OF COMMANDS
2.8.52 -ifft (+)
Arguments:
{ x
| y
| z }..{ x
| y
| z }
Compute the inverse fourier transform (real and imaginary parts) of selected images. optionally along the
specified axes only.
Tutorial page:
http://gmic.eu/tutorial/_fft.shtml
2.8.53 -ihaar
Arguments:
• scale>0
Compute the inverse haar multiscale wavelet transform of selected images.
2.8.54 -inn
Compute gradient-directed 2nd derivative of image(s).
Example 319 : image.jpg -inn
2.8.55 -inpaint (+)
Arguments:
• [mask]
• [mask],0,
fast
method
• [mask],
patch
size>=1,
lookup
size>=1,
lookup
factor>=0,
lookup
increment!=0,
blend
size>=0,0<=
blend
threshold<=1,
blend
decay>=0,
blend
scales>=1,
is
blend
outer={ 0
| 1
}
2.8. FILTERING
197
Inpaint selected images by specified mask.
If no patch size (or 0) is specified, inpainting is done using a fast average or median algorithm.
Otherwise, it used a patch-based reconstruction method, that can be very time consuming.
’fast
method’ can be { 0=low-connectivity average | 1=high-connectivity average | 2=low-connectivity
median | 3=high-connectivity median }.
Default values:
• ’patch
size=0’, ’fast
method=1’, ’lookup
size=22’, ’lookup
factor=0.5’,
’lookup
increment=1’, ’blend
size=0’, ’blend
threshold=0’, ’blend
decay=0.05’,
’blend
scales=10’ and ’is
blend
outer=1’.
Example 320 : image.jpg 100%,100% -ellipse 50%,50%,30,30,0,1,255 -ellipse
20%,20%,30,10,0,1,255 --inpaint..
[-1] -remove..
Example 321 : image.jpg 100%,100% -circle 30%,30%,30,1,255,0,255 -circle
70%,70%,50,1,255,0,255 --inpaint[0] [1],5,15,0.5,1,9,0 -remove[1]
2.8.56 -inpaint
flow
Arguments:
• [mask],
nb
global
iter>=0,
nb
local
iter>=0,
dt>0,
alpha>=0,
sigma>=0
198
CHAPTER 2. LIST OF COMMANDS
Apply iteration of the inpainting flow on selected images.
Default values:
• ’nb
global
iter=4’, ’nb
global
iter=15’, ’dt=10’, ’alpha=1’ and ’sigma=3’.
Example 322 : image.jpg 100%,100% -ellipse.
30%,30%,40,30,0,1,255 -inpaint
flow[0] [1]
2.8.57 -inpaint
holes
Arguments:
• maximal
area[%]>=0,
tolerance>=0,
is
high
connectivity={ 0
| 1 }
Inpaint all connected regions having an area less than specified value.
Default values:
• ’maximal
area=4’, ’tolerance=0’ and ’is
high
connectivity=0’.
Example 323 : image.jpg -noise 5%,2 --inpaint
holes 8,40
2.8. FILTERING
199
2.8.58 -inpaint
morpho
Arguments:
• [mask]
Inpaint selected images by specified mask using morphological operators.
Example 324 : image.jpg 100%,100% -ellipse.
30%,30%,40,30,0,1,255 --inpaint
morpho[0] [1]
2.8.59 -inpaint
patchmatch
Arguments:
• [mask],
nb
scales={ 0=auto
| >0
},
patch
size>0,
nb
iterations
per
scale>0,
blend
size>=0,
allow
outer
blending={ 0
| 1 },
is
already
initialized={ 0
| 1 }
Inpaint selected images by specified binary mask, using a multi-scale patchmatch algorithm.
Default values:
• ’nb
scales=0’, ’patch
size=9’, ’nb
iterations
per
scale=10’, ’blend
size=5’,
’allow
outer
blending=1’ and ’is
already
initialized=0’.
Example 325 : image.jpg 100%,100% -ellipse.
30%,30%,40,30,0,1,255 --inpaint
patchmatch[0] [1]
200
CHAPTER 2. LIST OF COMMANDS
2.8.60 -inpaint
diffusion
Arguments:
• [mask],
nb
scales[%]>=0,
diffusion
type={ 0=isotropic
| 1=delaunay-oriented
| 2=edge-oriented },
diffusion
iter>=0
Inpaint selected images by specified mask using a multiscale transport-diffusion algorithm.
Default values:
• ’smoothness=75%’, ’diffusion
type=1’ and ’diffusion
iter=20’.
Example 326 : image.jpg 100%,100% -ellipse.
30%,30%,40,30,0,1,255 --inpaint
diffusion[0] [1]
2.8.61 -kuwahara
Arguments:
• size>0
Apply Kuwahara filter of specified size on selected images.
Example 327 : image.jpg --kuwahara 5
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