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ENH: Add StructuralSimilarity Beta module (SSIM image filter) — stacked on #6085 #6034
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,29 @@ | ||
| # Modules/Beta/ | ||
| # | ||
| # In-tree home for modules that were formerly configure-time remote | ||
| # fetches (Modules/Remote/*.remote.cmake). Each module lives at | ||
| # Modules/Beta/<Name>/ with its own itk-module.cmake and is discovered | ||
| # automatically by the normal ITK module DAG scan (see | ||
| # CMake/ITKModuleEnablement.cmake). | ||
| # | ||
| # Alongside each ingested module, an optional manifest | ||
| # Modules/Beta/<Name>.beta.cmake records upstream provenance | ||
| # (UPSTREAM_URL, UPSTREAM_SHA at last ingest, INGEST_DATE, license, | ||
| # compliance level). The manifest files are inert at build time -- | ||
| # they are passive metadata consumed by tooling and human readers. | ||
|
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| # itk_beta_module_manifest() is a no-op that makes the *.beta.cmake | ||
| # files valid CMake so they can be include()-d by tooling without | ||
| # producing build-time side effects. | ||
| function(itk_beta_module_manifest _name) | ||
| # arguments are intentionally discarded; parsed by external tooling. | ||
| endfunction() | ||
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| # Include every *.beta.cmake so CMake at least syntactically validates | ||
| # them at configure time. This does not enable, build, or fetch anything. | ||
| file(GLOB _beta_manifests "${CMAKE_CURRENT_SOURCE_DIR}/*.beta.cmake") | ||
| foreach(_manifest ${_beta_manifests}) | ||
| include(${_manifest}) | ||
| endforeach() | ||
| unset(_beta_manifests) | ||
| unset(_manifest) |
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| itk_beta_module_manifest( | ||
| NAME StructuralSimilarity | ||
| UPSTREAM_URL "" | ||
| UPSTREAM_SHA "" | ||
| INGEST_DATE 2026-04-19 | ||
| LICENSE "Apache-2.0" | ||
| COMPLIANCE_LEVEL 3 | ||
| DESCRIPTION | ||
| "Structural Similarity Index (SSIM) image filter. New module | ||
| originally proposed against Modules/Filtering/ImageCompare; relocated to | ||
| Modules/Beta/ so the API can stabilize before promotion to a core | ||
| module." | ||
| ) |
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| project(StructuralSimilarity) | ||
| itk_module_impl() |
299 changes: 299 additions & 0 deletions
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Modules/Beta/StructuralSimilarity/include/itkStructuralSimilarityImageFilter.h
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| /*========================================================================= | ||
| * | ||
| * Copyright NumFOCUS | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * https://www.apache.org/licenses/LICENSE-2.0.txt | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| * | ||
| *=========================================================================*/ | ||
| #ifndef itkStructuralSimilarityImageFilter_h | ||
| #define itkStructuralSimilarityImageFilter_h | ||
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| #include "itkArray.h" | ||
| #include "itkImage.h" | ||
| #include "itkImageToImageFilter.h" | ||
| #include "itkNumericTraits.h" | ||
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| #include <type_traits> | ||
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| namespace itk | ||
| { | ||
| /** | ||
| * \class StructuralSimilarityImageFilter | ||
| * \brief Computes the Structural Similarity Index Measure (SSIM) between two images. | ||
| * | ||
| * This filter computes the Structural Similarity Index Measure | ||
| * \cite wang2004image between two input images of identical geometry. The | ||
| * output image stores the per-pixel SSIM map. The scalar mean SSIM over the | ||
| * valid (non-boundary) region is available via GetMeanSSIM() after Update(). | ||
| * | ||
| * \par Algorithm | ||
| * For two images \f$x\f$ and \f$y\f$, local statistics are computed by | ||
| * convolving with a discrete Gaussian kernel of standard deviation | ||
| * \f$\sigma\f$ (default 1.5): | ||
| * \f[ | ||
| * \mu_x = G_\sigma * x, \quad \mu_y = G_\sigma * y, | ||
| * \f] | ||
| * \f[ | ||
| * \sigma_x^2 = G_\sigma * x^2 - \mu_x^2,\quad | ||
| * \sigma_y^2 = G_\sigma * y^2 - \mu_y^2,\quad | ||
| * \sigma_{xy} = G_\sigma * (xy) - \mu_x \mu_y . | ||
| * \f] | ||
| * | ||
| * The three SSIM components are | ||
| * \f[ | ||
| * l(x,y) = \frac{2\mu_x\mu_y + C_1}{\mu_x^2 + \mu_y^2 + C_1}, \qquad | ||
| * c(x,y) = \frac{2\sigma_x\sigma_y + C_2}{\sigma_x^2 + \sigma_y^2 + C_2}, \qquad | ||
| * s(x,y) = \frac{\sigma_{xy} + C_3}{\sigma_x\sigma_y + C_3} | ||
| * \f] | ||
| * with \f$C_1 = (K_1 L)^2\f$, \f$C_2 = (K_2 L)^2\f$, \f$C_3 = C_2/2\f$, | ||
| * and \f$L\f$ the dynamic range of the pixel values. | ||
| * | ||
| * The combined SSIM is | ||
| * \f[ | ||
| * \mathrm{SSIM}(x,y) = [l(x,y)]^{\alpha}\,[c(x,y)]^{\beta}\,[s(x,y)]^{\gamma}. | ||
| * \f] | ||
| * | ||
| * With the default exponents \f$\alpha = \beta = \gamma = 1\f$ and the | ||
| * convention \f$C_3 = C_2/2\f$, this collapses to the simplified form | ||
| * \f[ | ||
| * \mathrm{SSIM}(x,y) = | ||
| * \frac{(2\mu_x\mu_y + C_1)\,(2\sigma_{xy} + C_2)} | ||
| * {(\mu_x^2 + \mu_y^2 + C_1)\,(\sigma_x^2 + \sigma_y^2 + C_2)} | ||
| * \f] | ||
| * which matches the reference implementation distributed by Wang et al. | ||
| * and the default behavior of \c skimage.metrics.structural_similarity . | ||
| * | ||
| * \par Properties | ||
| * - For identical images, the per-pixel SSIM is exactly 1 and the mean SSIM | ||
| * is exactly 1 (subject to floating-point precision). | ||
| * - The SSIM index is symmetric: \f$\mathrm{SSIM}(x,y) = \mathrm{SSIM}(y,x)\f$. | ||
| * - The SSIM index is bounded above by 1. In typical cases it is | ||
| * non-negative; values can be slightly negative for anti-correlated | ||
| * regions. | ||
| * | ||
| * \par Parameters | ||
| * - \c GaussianSigma: standard deviation of the Gaussian window | ||
| * (default 1.5, matching Wang et al.). | ||
| * - \c MaximumKernelWidth: hard limit on the discrete Gaussian kernel width | ||
| * (default 11, matching the canonical 11x11 window). | ||
| * - \c K1, \c K2: stability constants (defaults 0.01 and 0.03). | ||
| * - \c DynamicRange: \f$L\f$ in the formulas above; defaults to the dynamic | ||
| * range of the input pixel type via NumericTraits (e.g. 255 for | ||
| * \c unsigned char, 1.0 for \c float / \c double). For arbitrary | ||
| * floating-point images, set this explicitly to the actual data range. | ||
| * - \c LuminanceExponent (\f$\alpha\f$), \c ContrastExponent (\f$\beta\f$), | ||
| * \c StructureExponent (\f$\gamma\f$): defaults all 1.0. | ||
| * - \c ScaleWeights: array of per-scale weights for multi-scale SSIM | ||
| * (MS-SSIM, \cite wang2003multiscale). When the array contains a single | ||
| * element (the default), the filter computes ordinary single-scale SSIM. | ||
| * Multi-scale evaluation with more than one scale is not yet implemented | ||
| * and will raise an exception in BeforeGenerate. | ||
| * | ||
| * The filter is N-dimensional, multi-threaded, and templated over the input | ||
| * and output image types. The output pixel type defaults to \c float. | ||
| * | ||
| * \sa SimilarityIndexImageFilter | ||
| * \sa DiscreteGaussianImageFilter | ||
| * | ||
| * \ingroup MultiThreaded | ||
| * \ingroup StructuralSimilarity | ||
| */ | ||
| template <typename TInputImage, typename TOutputImage = Image<float, TInputImage::ImageDimension>> | ||
| class ITK_TEMPLATE_EXPORT StructuralSimilarityImageFilter : public ImageToImageFilter<TInputImage, TOutputImage> | ||
|
hjmjohnson marked this conversation as resolved.
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| { | ||
| public: | ||
| ITK_DISALLOW_COPY_AND_MOVE(StructuralSimilarityImageFilter); | ||
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| /** Standard class type aliases. */ | ||
| using Self = StructuralSimilarityImageFilter; | ||
| using Superclass = ImageToImageFilter<TInputImage, TOutputImage>; | ||
| using Pointer = SmartPointer<Self>; | ||
| using ConstPointer = SmartPointer<const Self>; | ||
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| /** Method for creation through the object factory. */ | ||
| itkNewMacro(Self); | ||
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| /** \see LightObject::GetNameOfClass() */ | ||
| itkOverrideGetNameOfClassMacro(StructuralSimilarityImageFilter); | ||
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| /** Image type aliases. */ | ||
| using InputImageType = TInputImage; | ||
| using OutputImageType = TOutputImage; | ||
| using InputPixelType = typename InputImageType::PixelType; | ||
| using OutputPixelType = typename OutputImageType::PixelType; | ||
| using InputImageRegionType = typename InputImageType::RegionType; | ||
| using OutputImageRegionType = typename OutputImageType::RegionType; | ||
| using SizeType = typename InputImageType::SizeType; | ||
| using IndexType = typename InputImageType::IndexType; | ||
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| static constexpr unsigned int ImageDimension = InputImageType::ImageDimension; | ||
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| /** Floating-point type used for all SSIM computations. */ | ||
| using RealType = typename NumericTraits<InputPixelType>::RealType; | ||
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| /** Type used for the user-specified array of multi-scale weights. */ | ||
| using ScaleWeightsType = Array<RealType>; | ||
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| /** Set/Get the first input image. */ | ||
| /** @ITKStartGrouping */ | ||
| void | ||
| SetInput1(const InputImageType * image) | ||
| { | ||
| this->SetInput(image); | ||
| } | ||
| const InputImageType * | ||
| GetInput1() const | ||
| { | ||
| return this->GetInput(0); | ||
| } | ||
| /** @ITKEndGrouping */ | ||
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| /** Set/Get the second input image. */ | ||
| /** @ITKStartGrouping */ | ||
| void | ||
| SetInput2(const InputImageType * image); | ||
| const InputImageType * | ||
| GetInput2() const; | ||
| /** @ITKEndGrouping */ | ||
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| /** Standard deviation \f$\sigma\f$ of the Gaussian window used to compute | ||
| * local statistics. Default 1.5 (matching Wang et al. 2004). */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(GaussianSigma, double); | ||
| itkGetConstMacro(GaussianSigma, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** Maximum width (per dimension) of the discrete Gaussian kernel. | ||
| * Default 11, giving an 11x11 window in 2D when sigma=1.5. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(MaximumKernelWidth, unsigned int); | ||
| itkGetConstMacro(MaximumKernelWidth, unsigned int); | ||
| /** @ITKEndGrouping */ | ||
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| /** \f$K_1\f$ stability constant. Default 0.01. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(K1, double); | ||
| itkGetConstMacro(K1, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** \f$K_2\f$ stability constant. Default 0.03. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(K2, double); | ||
| itkGetConstMacro(K2, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** Dynamic range \f$L\f$ of the pixel values used to compute | ||
| * \f$C_1 = (K_1 L)^2\f$ and \f$C_2 = (K_2 L)^2\f$. Default depends on | ||
| * the input pixel type: 255 for \c unsigned \c char, 65535 for | ||
| * \c unsigned \c short, 1.0 for \c float / \c double, etc. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(DynamicRange, double); | ||
| itkGetConstMacro(DynamicRange, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** Exponent \f$\alpha\f$ on the luminance term. Default 1.0. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(LuminanceExponent, double); | ||
| itkGetConstMacro(LuminanceExponent, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** Exponent \f$\beta\f$ on the contrast term. Default 1.0. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(ContrastExponent, double); | ||
| itkGetConstMacro(ContrastExponent, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** Exponent \f$\gamma\f$ on the structure term. Default 1.0. */ | ||
| /** @ITKStartGrouping */ | ||
| itkSetMacro(StructureExponent, double); | ||
| itkGetConstMacro(StructureExponent, double); | ||
| /** @ITKEndGrouping */ | ||
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| /** Per-scale weights for multi-scale SSIM (MS-SSIM). An array of size 1 | ||
| * (the default) requests ordinary single-scale SSIM and is the only | ||
| * configuration currently supported. Setting an array of length greater | ||
| * than 1 will currently raise an exception in BeforeGenerate. */ | ||
| /** @ITKStartGrouping */ | ||
| void | ||
| SetScaleWeights(const ScaleWeightsType & weights); | ||
| itkGetConstReferenceMacro(ScaleWeights, ScaleWeightsType); | ||
| /** @ITKEndGrouping */ | ||
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| /** Mean SSIM over the valid (non-Gaussian-padded) region. Available | ||
| * after Update(). */ | ||
| itkGetConstMacro(MeanSSIM, double); | ||
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| itkConceptMacro(InputHasNumericTraitsCheck, (Concept::HasNumericTraits<InputPixelType>)); | ||
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| protected: | ||
| StructuralSimilarityImageFilter(); | ||
| ~StructuralSimilarityImageFilter() override = default; | ||
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| void | ||
| PrintSelf(std::ostream & os, Indent indent) const override; | ||
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| /** Verify that parameters are valid and both inputs are set with matching regions. */ | ||
| void | ||
| VerifyPreconditions() const override; | ||
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| /** This filter requires its full input to compute correct mean SSIM. */ | ||
| void | ||
| GenerateInputRequestedRegion() override; | ||
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| /** This filter computes the full output. */ | ||
| void | ||
| EnlargeOutputRequestedRegion(DataObject * data) override; | ||
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| /** Composite-filter-style: drives the internal sub-pipeline (5 Gaussian | ||
| * convolutions plus a parallelized SSIM combination). */ | ||
| void | ||
| GenerateData() override; | ||
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| private: | ||
| double m_GaussianSigma{ 1.5 }; | ||
| unsigned int m_MaximumKernelWidth{ 11 }; | ||
| double m_K1{ 0.01 }; | ||
| double m_K2{ 0.03 }; | ||
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| /** Default dynamic range: 1.0 for floating-point pixels (assume normalized | ||
| * data), and \c NumericTraits::max() - \c NumericTraits::min() for integer | ||
| * pixels (e.g. 255 for \c unsigned \c char). */ | ||
| static constexpr double | ||
| DefaultDynamicRange() | ||
| { | ||
| if constexpr (std::is_floating_point_v<InputPixelType>) | ||
| { | ||
| return 1.0; | ||
| } | ||
| else | ||
| { | ||
| return static_cast<double>(NumericTraits<InputPixelType>::max()) - | ||
| static_cast<double>(NumericTraits<InputPixelType>::min()); | ||
| } | ||
| } | ||
| double m_DynamicRange{ DefaultDynamicRange() }; | ||
| double m_LuminanceExponent{ 1.0 }; | ||
| double m_ContrastExponent{ 1.0 }; | ||
| double m_StructureExponent{ 1.0 }; | ||
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| ScaleWeightsType m_ScaleWeights{}; | ||
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| double m_MeanSSIM{ 0.0 }; | ||
| }; | ||
| } // end namespace itk | ||
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| #ifndef ITK_MANUAL_INSTANTIATION | ||
| # include "itkStructuralSimilarityImageFilter.hxx" | ||
| #endif | ||
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| #endif | ||
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