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2.8. FILTERING
201
2.8.62 -laplacian
ComputeLaplacianofselectedimages.
Example328:image.jpg -laplacian
2.8.63 -lic
Arguments:
amplitude>0,
channels>0
Render LIC representation of selected vector fields.
Default values:
• ’amplitude=30’ and ’channels=1’.
Example 329 : 400,400,1,2,’if(c==0,x-w/2,y-h/2)’ --lic 200,3 -quiver..
[-2],10,-13,1,1,255
2.8.64 -map
tones
Arguments:
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202
CHAPTER 2. LIST OF COMMANDS
threshold>=0,
gamma>=0,
smoothness>=0,nb
iter>=0
Apply tone mapping operator on selected images, based on Poisson equation.
Default values:
• ’threshold=0.1’, ’gamma=0.8’, ’smoothness=0.5’ and ’nb
iter=30’.
Example330 : image.jpg --map
tones ,
2.8.65 -map
tones
fast
Arguments:
radius[%]>=0,
power>=0
Apply fast tone mappingoperator on selected images.
Default values:
• ’radius=3%’ and ’power=0.3’.
Example 331 : image.jpg --map
tones
fast ,
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2.8. FILTERING
203
2.8.66 -meancurvature
flow
Arguments:
nb
iter>=0,
dt,
keep
sequence={ 0
| 1 }
Apply iterations of the mean curvature flow on selected images.
Default values:
• ’nb
iter=10’, ’dt=30’ and ’keep
sequence=0’.
Example332 : image.jpg --meancurvature
flow 20
2.8.67 -median (+)
Arguments:
• size>=0,
threshold>0
Apply (opt. thresholded) median filter on selected images with structuring element size x size.
Example 333 : image.jpg --median 5
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204
CHAPTER 2. LIST OF COMMANDS
2.8.68 -nlmeans
Arguments:
patch
radius>0,
spatial
bandwidth>0,
tonal
bandwidth>0,
patch
measure
command
Apply non local means denoising of Buades et al, 2005. on selected images.
The patch is a gaussian function of ’std
patch
radius’.
The spatial kernel is a rectangle of radius ’spatial
bandwidth’.
The tonal kernelis exponential (exp(-dˆ2/
tonal
bandwidthˆ2)) with d the euclidiean distance between image
patches.
Default values:
• ’patch
radius=4’, ’spatial
bandwidth=4’, ’tonal
bandwidth=10’ and
’patch
measure
command=-norm’.
Example 334 : image.jpg --noise 10 -nlmeans.
4,4,{0.6
*
${-std
noise}}
2.8.69 -nlmeans
core
Arguments:
reference
image,
scaling
map,
patch
radius>0,
spatial
bandwidth>0
Apply non local means denoising using a image for weigth and a map for scaling
2.8.70 -normalize
local
Arguments:
amplitude>=0,
radius>0,
n
smooth>=0[%],
a
smooth>=0[%],
is
cut={ 0
| 1
},
min=0,
max=255
Normalize selected images locally.
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2.8. FILTERING
205
Default values:
• ’amplitude=3’, ’radius=16’, ’n
smooth=4%’, ’a
smooth=2%’, ’is
cut=1’, ’min=0’
and ’max=255’.
Example 335 : image.jpg --normalize
local 8,10
2.8.71 -normalized
cross
correlation
Arguments:
• [mask]
Compute normalized cross-correlation of selected images with specified mask.
Example336 :image.jpg --shift -30,-20 --normalized
cross
correlation[0] [1]
2.8.72 -peronamalik
flow
Arguments:
• K
factor>0,
nb
iter>=0,
dt,
keep
sequence={ 0
| 1 }
Apply iterations of the Perona-Malik flow on selected images.
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206
CHAPTER 2. LIST OF COMMANDS
Default values:
• ’K
factor=20’, ’nb
iter=5’, ’dt=5’ and ’keep
sequence=0’.
Example337 :image.jpg --heat
flow 20
2.8.73 -phase
correlation
Arguments:
• [destination]
Estimate translation vector between selected source images and specified destination.
Example 338 : image.jpg --shift -30,-20 --phase
correlation[0] [1] -unroll.
y
2.8.74 -pde
flow
Arguments:
nb
iter>=0,
dt,
velocity
command,
keep
sequence={ 0
| 1 }
Apply iterations of a generic PDE flow on selected images.
2.8. FILTERING
207
Default values:
• ’nb
iter=10’, ’dt=30’, ’velocity
command=laplacian’ and ’keep
sequence=0’.
Example339 : image.jpg --pde
flow 20
2.8.75 -periodize
poisson
Periodize selected images using a Poisson solver in Fourier space.
Example 340 : image.jpg --periodize
poisson -array 2,2,2
2.8.76 -red
eye
Arguments:
• 0<=
threshold<=100,
smoothness>=0,0<=attenuation<=1
Attenuate red-eye effect in selectedimages.
Default values:
• ’threshold=75’, ’smoothness=3.5’ and ’attenuation=0.1’.
208
CHAPTER 2. LIST OF COMMANDS
Example 341 : image.jpg --red
eye ,
2.8.77 -remove
hotpixels
Arguments:
mask
size>0,
threshold[%]>0
Remove hot pixels in selected images.
Default values:
• ’mask
size=3’ and ’threshold=10%’.
Example 342 : image.jpg -noise 10,2 --remove
hotpixels ,
2.8.78 -remove
pixels
Arguments:
• number
of
pixels[%]>=0
Remove specified number of pixels (i.e. set them to 0) from the set of non-zero pixels in selected images.
2.8. FILTERING
209
Example343 : image.jpg --remove
pixels 50%
2.8.79 -sharpen (+)
Arguments:
• amplitude>=0
• amplitude>=0,edge>=0,
alpha,
sigma
Sharpen selected images by inverse diffusion or shock filters methods.
’edge’ must be specified to enable shock-filter method.
Default values:
• ’alpha=0’ and ’sigma=0’.
Example344 :image.jpg --sharpen 300
210
CHAPTER 2. LIST OF COMMANDS
Example 345 : image.jpg -blur 5 --sharpen.
300,1
2.8.80 -smooth (+)
Arguments:
• amplitude>=0,
sharpness>=0,
anisotropy,
alpha,
sigma,
dl>0,
da>0,
precision>0,interpolation,
fast
approx={ 0
| 1
}
• nb
iterations>=0,
sharpness>=0,
anisotropy,
alpha,
sigma,
dt>0,0
• [tensor
field],
amplitude>=0,
dl>0,
da>0,
precision>0,
interpolation,
fast
approx={ 0
| 1
}
• [tensor
field],
nb
iters>=0,
dt>0,0
Smooth selected images anisotropically using diffusion PDE’s, with specified field of diffusion tensors.
’anisotropy’ must be in [0,1].
’interpolation’ can be { 0=nearest | 1=linear | 2=runge-kutta }.
Default values:
• ’sharpness=0.7’, ’anisotropy=0.3’, ’alpha=0.6’, ’sigma=1.1’, ’dl=0.8’,
’da=30’, ’precision=2’, ’interpolation=0’ and ’fast
approx=1’.
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