From bd6205aa69e1090927afe695e6229cd0bbed97ff Mon Sep 17 00:00:00 2001
From: Stephan Hilb <stephan@ecshi.net>
Date: Sun, 17 May 2020 13:41:19 +0200
Subject: [PATCH] =?UTF-8?q?extend=20chambolle=20to=20local=20varying=20?=
=?UTF-8?q?=CE=BB?=
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---
src/chambolle.jl | 19 +++++++++++--------
src/types.jl | 6 ++++--
2 files changed, 15 insertions(+), 10 deletions(-)
diff --git a/src/chambolle.jl b/src/chambolle.jl
index 370e7c4..2844098 100644
--- a/src/chambolle.jl
+++ b/src/chambolle.jl
@@ -4,8 +4,8 @@
# https://doi.org/10.1023/B:JMIV.0000011325.36760.1e
#
# Implementation Notes:
-# - TV-parameter α instead of λ
-# - feasibility constraint |p|<=α instead of |p|<=1
+# - λ is not a scalar but a scalar field
+# - pointwise feasibility constraint |p|<=λ instead of |p|<=1
# - B is introduced, the original Chambolle algorithm has B=Id
using Base: @_inline_meta
@@ -21,13 +21,15 @@ struct ChambolleAlgorithm <: Algorithm
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::M
"algorithm data"
algorithm::A
"matrix view on model.f"
g::G
+ "matrix view on model.λ"
+ λ::Λ
"matrix view on pv"
p::T
"matrix view on rv"
@@ -40,13 +42,14 @@ struct ChambolleContext{M,A,G,T,R,S,Sv,K1,K2} <: Context
sv::Sv
"div(p) + g kernel"
k1::K1
- "(p + τ*grad(q))/(1 + τ/α|grad(q)|) kernel"
+ "(p + τ*grad(q))/(1 + τ/λ|grad(q)|) kernel"
k2::K2
end
-function init(md::ChambolleModel, alg::ChambolleAlgorithm)
+function init(md::OpROFModel, alg::ChambolleAlgorithm)
d = ndims(md.g)
g = extend(md.g, StaticKernels.ExtensionNothing())
+ λ = extend(md.λ, StaticKernels.ExtensionNothing())
pv = zeros(d * length(md.g))
rv = zeros(length(md.g))
sv = zero(rv)
@@ -60,11 +63,11 @@ function init(md::ChambolleModel, alg::ChambolleAlgorithm)
@inline function kf2(pw, 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
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
@generated function gradient(w::StaticKernels.Window{<:Any,N}) where N
@@ -98,7 +101,7 @@ function step!(ctx::ChambolleContext)
map!(ctx.k1, ctx.r, ctx.p, ctx.g)
# s = B * r
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)
end
diff --git a/src/types.jl b/src/types.jl
index 2db8925..f80834c 100644
--- a/src/types.jl
+++ b/src/types.jl
@@ -30,11 +30,13 @@ struct DualTVDDModel{U,VV} <: Model
end
"min_p 1/2 * |div(p) - g|_B^2 + χ_{|p|<=λ}"
-struct ChambolleModel{U,VV} <: Model
+struct OpROFModel{U,VV,Λ} <: Model
"given data"
g::U
"B norm operator"
B::VV
"total variation parameter"
- λ::Float64
+ λ::Λ
end
+
+OpROFModel(g, B, λ::Real) = OpROFModel(g, B, fill!(similar(g, typeof(λ)), λ))
--
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