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DualTVDD.jl
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Stephan Hilb
DualTVDD.jl
Commits
bd6205aa
Commit
bd6205aa
authored
5 years ago
by
Stephan Hilb
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extend chambolle to local varying λ
parent
f33d13b8
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2 changed files
src/chambolle.jl
+11
-8
11 additions, 8 deletions
src/chambolle.jl
src/types.jl
+4
-2
4 additions, 2 deletions
src/types.jl
with
15 additions
and
10 deletions
src/chambolle.jl
+
11
−
8
View file @
bd6205aa
...
@@ -4,8 +4,8 @@
...
@@ -4,8 +4,8 @@
# https://doi.org/10.1023/B:JMIV.0000011325.36760.1e
# https://doi.org/10.1023/B:JMIV.0000011325.36760.1e
#
#
# Implementation Notes:
# Implementation Notes:
# -
TV-parameter α instead of λ
# -
λ is not a scalar but a scalar field
# - feasibility constraint |p|<=
α
instead of |p|<=1
# -
pointwise
feasibility constraint |p|<=
λ
instead of |p|<=1
# - B is introduced, the original Chambolle algorithm has B=Id
# - B is introduced, the original Chambolle algorithm has B=Id
using
Base
:
@_inline_meta
using
Base
:
@_inline_meta
...
@@ -21,13 +21,15 @@ struct ChambolleAlgorithm <: Algorithm
...
@@ -21,13 +21,15 @@ struct ChambolleAlgorithm <: Algorithm
end
end
end
end
struct
ChambolleContext
{
M
,
A
,
G
,
T
,
R
,
S
,
Sv
,
K1
,
K2
}
<:
Context
struct
ChambolleContext
{
M
,
A
,
G
,
Λ
,
T
,
R
,
S
,
Sv
,
K1
,
K2
}
<:
Context
"model data"
"model data"
model
::
M
model
::
M
"algorithm data"
"algorithm data"
algorithm
::
A
algorithm
::
A
"matrix view on model.f"
"matrix view on model.f"
g
::
G
g
::
G
"matrix view on model.λ"
λ
::
Λ
"matrix view on pv"
"matrix view on pv"
p
::
T
p
::
T
"matrix view on rv"
"matrix view on rv"
...
@@ -40,13 +42,14 @@ struct ChambolleContext{M,A,G,T,R,S,Sv,K1,K2} <: Context
...
@@ -40,13 +42,14 @@ struct ChambolleContext{M,A,G,T,R,S,Sv,K1,K2} <: Context
sv
::
Sv
sv
::
Sv
"div(p) + g kernel"
"div(p) + g kernel"
k1
::
K1
k1
::
K1
"(p + τ*grad(q))/(1 + τ/
α
|grad(q)|) kernel"
"(p + τ*grad(q))/(1 + τ/
λ
|grad(q)|) kernel"
k2
::
K2
k2
::
K2
end
end
function
init
(
md
::
Chambolle
Model
,
alg
::
ChambolleAlgorithm
)
function
init
(
md
::
OpROF
Model
,
alg
::
ChambolleAlgorithm
)
d
=
ndims
(
md
.
g
)
d
=
ndims
(
md
.
g
)
g
=
extend
(
md
.
g
,
StaticKernels
.
ExtensionNothing
())
g
=
extend
(
md
.
g
,
StaticKernels
.
ExtensionNothing
())
λ
=
extend
(
md
.
λ
,
StaticKernels
.
ExtensionNothing
())
pv
=
zeros
(
d
*
length
(
md
.
g
))
pv
=
zeros
(
d
*
length
(
md
.
g
))
rv
=
zeros
(
length
(
md
.
g
))
rv
=
zeros
(
length
(
md
.
g
))
sv
=
zero
(
rv
)
sv
=
zero
(
rv
)
...
@@ -60,11 +63,11 @@ function init(md::ChambolleModel, alg::ChambolleAlgorithm)
...
@@ -60,11 +63,11 @@ function init(md::ChambolleModel, alg::ChambolleAlgorithm)
@inline
function
kf2
(
pw
,
sw
)
@inline
function
kf2
(
pw
,
sw
)
sgrad
=
alg
.
τ
*
gradient
(
sw
)
sgrad
=
alg
.
τ
*
gradient
(
sw
)
return
@inbounds
(
pw
[
z
]
+
sgrad
)
/
(
1
+
norm
(
sgrad
)
/
md
.
λ
)
return
@inbounds
(
pw
[
z
]
+
sgrad
)
/
(
1
+
norm
(
sgrad
)
/
λ
[
pw
.
position
]
)
end
end
k2
=
Kernel
{
ntuple
(
_
->
0
:
1
,
d
)}(
kf2
)
k2
=
Kernel
{
ntuple
(
_
->
0
:
1
,
d
)}(
kf2
)
return
ChambolleContext
(
md
,
alg
,
g
,
p
,
r
,
s
,
rv
,
sv
,
k1
,
k2
)
return
ChambolleContext
(
md
,
alg
,
g
,
λ
,
p
,
r
,
s
,
rv
,
sv
,
k1
,
k2
)
end
end
@generated
function
gradient
(
w
::
StaticKernels
.
Window
{
<:
Any
,
N
})
where
N
@generated
function
gradient
(
w
::
StaticKernels
.
Window
{
<:
Any
,
N
})
where
N
...
@@ -98,7 +101,7 @@ function step!(ctx::ChambolleContext)
...
@@ -98,7 +101,7 @@ function step!(ctx::ChambolleContext)
map!
(
ctx
.
k1
,
ctx
.
r
,
ctx
.
p
,
ctx
.
g
)
map!
(
ctx
.
k1
,
ctx
.
r
,
ctx
.
p
,
ctx
.
g
)
# s = B * r
# s = B * r
mul!
(
ctx
.
sv
,
ctx
.
model
.
B
,
ctx
.
rv
)
mul!
(
ctx
.
sv
,
ctx
.
model
.
B
,
ctx
.
rv
)
# p = (p + τ*grad(s)) / (1 + τ/
α
|grad(s)|)
# p = (p + τ*grad(s)) / (1 + τ/
λ
|grad(s)|)
map!
(
ctx
.
k2
,
ctx
.
p
,
ctx
.
p
,
ctx
.
s
)
map!
(
ctx
.
k2
,
ctx
.
p
,
ctx
.
p
,
ctx
.
s
)
end
end
...
...
This diff is collapsed.
Click to expand it.
src/types.jl
+
4
−
2
View file @
bd6205aa
...
@@ -30,11 +30,13 @@ struct DualTVDDModel{U,VV} <: Model
...
@@ -30,11 +30,13 @@ struct DualTVDDModel{U,VV} <: Model
end
end
"min_p 1/2 * |div(p) - g|_B^2 + χ_{|p|<=λ}"
"min_p 1/2 * |div(p) - g|_B^2 + χ_{|p|<=λ}"
struct
Chambolle
Model
{
U
,
VV
}
<:
Model
struct
OpROF
Model
{
U
,
VV
,
Λ
}
<:
Model
"given data"
"given data"
g
::
U
g
::
U
"B norm operator"
"B norm operator"
B
::
VV
B
::
VV
"total variation parameter"
"total variation parameter"
λ
::
Float64
λ
::
Λ
end
end
OpROFModel
(
g
,
B
,
λ
::
Real
)
=
OpROFModel
(
g
,
B
,
fill!
(
similar
(
g
,
typeof
(
λ
)),
λ
))
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