Add BM3D(sparse 3D transform-domain collaborative filtering) denoisin…

…g algorithm (#21)

Project.toml

@@ -4,12 +4,15 @@ authors = ["Johnny Chen <[email protected]>"]
 version = "0.1.2"
 
 [deps]
+BM3DDenoise = "95fb3b36-088a-43fb-bb1b-b1f34fadbd7d"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 ImageCore = "a09fc81d-aa75-5fe9-8630-4744c3626534"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
+UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
 [compat]
+BM3DDenoise = "1.0.1"
 Distributions = "0.19, 0.20, 0.21, 0.22, 0.23, 0.24, 0.25"
 ImageCore = "0.9"
 Reexport = "0.2, 1.0"

docs/examples/reduce_noise/BM3D.jl

@@ -0,0 +1,32 @@
+# ---
+# title: The BM3D(sparse 3D transform-domain collaborative filtering) denoising algorithm.
+# id: bm3d-demo
+# cover: assets/bm3d_cover.png
+# date: 2021-08-04
+# author: "[Longhao Chen](https:/Longhao-Chen)"
+# description: Use the BM3D denoising algorithm to reduce gaussian noise
+# ---
+
+using ImageNoise
+using TestImages, ImageShow, ImageCore, ImageQualityIndexes, ImageTransformations
+using FileIO, Random #src
+
+# First, load an image and and add gaussian noise to it
+
+gray_img = float.(imresize(testimage("cameraman"), ratio=0.5))
+n = AdditiveWhiteGaussianNoise(0.1)
+noisy_img = apply_noise(gray_img, n)
+
+# Then calling the standard `reduce_noise` API
+
+f_bm3d = BM3D(0.1)
+denoised_img = reduce_noise(noisy_img, f_bm3d)
+
+mosaicview(gray_img, noisy_img, denoised_img; nrow=1)
+
+# Get the PSNR using ImageQualityIndexes package:
+
+assess_psnr(gray_img, denoised_img)
+
+mkpath("assets") #src
+save("assets/bm3d_cover.png", denoised_img) #src

src/ReduceNoise/BM3DDenoise.jl

@@ -0,0 +1,55 @@
+using UUIDs
+const BM3DDenoise = Base.PkgId(UUID("95fb3b36-088a-43fb-bb1b-b1f34fadbd7d"), "BM3DDenoise")
+
+# Rewrite from ImageIO.jl
+function checked_import(pkgid)
+ Base.root_module_exists(pkgid) && return Base.root_module(pkgid)
+ # If not available, load the library or throw an error.
+ Base.require(pkgid)
+end
+
+
+@doc raw"""
+ BM3D(σ [, config=bm3d_config()])
+
+The BM3D(sparse 3D transform-domain collaborative filtering) denoising algorithm.
+
+# Arguments
+
+* `σ::Float64` is the variance of the noise.
+
+* `config::bm3d_config` is `BM3DDenoise.bm3d_config`.
+
+# Examples
+
+```julia
+img = testimage("lena_color_256")
+
+n = AdditiveWhiteGaussianNoise(0.1)
+noisy_img = apply_noise(img, n)
+
+# use default arguments
+f_denoise = BM3D(0.1)
+denoised_img = reduce_noise(noisy_img, f_denoise)
+```
+
+See also: [`reduce_noise`](@ref), [`reduce_noise!`](@ref)
+"""
+struct BM3D <: AbstractImageDenoiseAlgorithm
+ """degree of filtering"""
+ σ::Float64
+ """bm3d_config"""
+ config
+ function BM3D(σ, config)
+ σ > 0 || @warn "σ is supposed to be positive"
+ new(σ, config)
+ end
+end
+BM3D(σ) = BM3D(σ, Base.invokelatest(checked_import(BM3DDenoise).bm3d_config))
+
+function (f::BM3D)(out::AbstractArray{T},
+ img::AbstractArray) where T
+ axes(out) == axes(img) || ArgumentError("Images should have the same axes.")
+ out .= T.(Base.invokelatest(checked_import(BM3DDenoise).bm3d, img, f.σ, f.config))
+ return out
+end

src/ReduceNoise/ReduceNoise.jl

@@ -9,11 +9,14 @@ using ImageCore: NumberLike, GenericGrayImage, GenericImage
 import ..NoiseAPI: AbstractImageDenoiseAlgorithm, reduce_noise, reduce_noise!
 
 include("compat.jl")
+include("BM3DDenoise.jl")
 include("NonlocalMean.jl")
 
 export
  reduce_noise, reduce_noise!,
 
+ # BM3D
+ BM3D,
  # Non-local mean filter for gaussian noise
  NonlocalMean, get_NonlocalMean_rp
 

test/ReduceNoise/BM3DDenoise.jl

@@ -0,0 +1,14 @@
+@testset "BM3DDenoise" begin
+ @info "Test: BM3DDenoise"
+ @testset "Numeric" begin
+ img_gray = n0f8.(imresize(testimage("lena_gray_256"); ratio=0.25))
+ n = AdditiveWhiteGaussianNoise(0.05)
+ noisy_img = apply_noise(img_gray, n; rng=MersenneTwister(0))
+
+ f = BM3D(0.05)
+ denoised_img = reduce_noise(noisy_img, f)
+ # further modification shall not decrease psnr and ssim
+ @test assess(PSNR(), denoised_img, img_gray) >= 28.
+ @test assess(SSIM(), denoised_img, img_gray) >= 0.9
+ end
+end

test/runtests.jl

@@ -12,6 +12,7 @@ include("ApplyNoise/AdditiveWhiteGaussianNoise.jl")
 # ReduceNoise
 @info "Test: ReduceNoise"
 include("ReduceNoise/NonlocalMean.jl")
+include("ReduceNoise/BM3DDenoise.jl")
 end
 
 nothing