1 /*========================================================================= 2 * 3 * Copyright Insight Software Consortium 4 * 5 * Licensed under the Apache License, Version 2.0 (the "License"); 6 * you may not use this file except in compliance with the License. 7 * You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0.txt 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 * 17 *=========================================================================*/ 18 #ifndef itkHistogramImageToImageMetric_h 19 #define itkHistogramImageToImageMetric_h 20 21 #include "itkHistogram.h" 22 #include "itkImageToImageMetric.h" 23 24 namespace itk 25 { 26 /** \class HistogramImageToImageMetric 27 \brief Computes similarity between two objects to be registered 28 29 This class is templated over the type of the fixed and moving 30 images to be compared. 31 32 The metric computes the similarity measure between pixels in the 33 moving image and pixels in the fixed image using a histogram. 34 35 \ingroup RegistrationMetrics 36 * \ingroup ITKRegistrationCommon 37 */ 38 template< typename TFixedImage, typename TMovingImage > 39 class ITK_TEMPLATE_EXPORT HistogramImageToImageMetric: 40 public ImageToImageMetric< TFixedImage, TMovingImage > 41 { 42 public: 43 ITK_DISALLOW_COPY_AND_ASSIGN(HistogramImageToImageMetric); 44 45 /** Standard class type aliases. */ 46 using Self = HistogramImageToImageMetric; 47 using Superclass = ImageToImageMetric< TFixedImage, TMovingImage >; 48 using Pointer = SmartPointer< Self >; 49 using ConstPointer = SmartPointer< const Self >; 50 51 /** Run-time type information (and related methods). */ 52 itkTypeMacro(HistogramImageToImageMetric, ImageToImageMetric); 53 54 /** Types transferred from the base class */ 55 using RealType = typename Superclass::RealType; 56 using TransformType = typename Superclass::TransformType; 57 using TransformPointer = typename Superclass::TransformPointer; 58 using TransformParametersType = typename Superclass::TransformParametersType; 59 using TransformJacobianType = typename Superclass::TransformJacobianType; 60 using GradientPixelType = typename Superclass::GradientPixelType; 61 using InputPointType = typename Superclass::InputPointType; 62 using OutputPointType = typename Superclass::OutputPointType; 63 using MeasureType = typename Superclass::MeasureType; 64 using DerivativeType = typename Superclass::DerivativeType; 65 using FixedImageType = typename Superclass::FixedImageType; 66 using FixedImagePixelType = typename Superclass::FixedImageType::PixelType; 67 using MovingImageType = typename Superclass::MovingImageType; 68 using MovingImagePixelType = typename Superclass::MovingImageType::PixelType; 69 using FixedImageConstPointerType = typename Superclass::FixedImageConstPointer; 70 using MovingImageConstPointerType = typename Superclass::MovingImageConstPointer; 71 72 /** Typedefs for histogram. This should have been defined as 73 Histogram<RealType,2> but a bug in VC++7 produced an internal compiler 74 error with such declaration. */ 75 using HistogramType = Statistics::Histogram< double >; 76 77 using MeasurementVectorType = typename HistogramType::MeasurementVectorType; 78 using HistogramSizeType = typename HistogramType::SizeType; 79 using HistogramPointer = typename HistogramType::Pointer; 80 81 /** Initializes the metric. */ 82 void Initialize() override; 83 84 /** Define the transform and thereby the parameter space of the metric 85 * and the space of its derivatives */ 86 void SetTransform(TransformType *transform) override; 87 88 /** Sets the histogram size. Note this function must be called before 89 \c Initialize(). */ 90 itkSetMacro(HistogramSize, HistogramSizeType); 91 92 /** Gets the histogram size. */ 93 itkGetConstReferenceMacro(HistogramSize, HistogramSizeType); 94 95 /** Factor to increase the upper bound for the samples in the histogram. 96 Default value is 0.001 */ 97 itkSetMacro(UpperBoundIncreaseFactor, double); 98 itkGetConstMacro(UpperBoundIncreaseFactor, double); 99 100 /** The padding value. */ 101 itkSetMacro(PaddingValue, FixedImagePixelType); 102 103 /** Returns the padding value. */ 104 itkGetConstReferenceMacro(PaddingValue, FixedImagePixelType); 105 106 /** Return the joint histogram. This is updated during every call to the 107 * GetValue() method. The histogram can for instance be used by 108 * itk::HistogramToImageFilter to plot the joint histogram. */ 109 itkGetConstReferenceMacro(Histogram, HistogramPointer); 110 111 /** Set whether the padding value should be used to determine which pixels 112 should be ignored when calculating the similarity measure. Those pixels 113 in the fixed image which have the padding value will be ignored. */ 114 itkSetMacro(UsePaddingValue, bool); 115 itkGetConstMacro(UsePaddingValue, bool); 116 117 /** Sets the step length used to calculate the derivative. */ 118 itkSetMacro(DerivativeStepLength, double); 119 120 /** Returns the step length used to calculate the derivative. */ 121 itkGetConstMacro(DerivativeStepLength, double); 122 123 /** The scales type. */ 124 using ScalesType = Array< double >; 125 126 /** Sets the derivative step length scales. */ 127 itkSetMacro(DerivativeStepLengthScales, ScalesType); 128 129 /** Returns the derivate step length scales. */ 130 itkGetConstReferenceMacro(DerivativeStepLengthScales, ScalesType); 131 132 /** Get the value for single valued optimizers. */ 133 MeasureType GetValue(const TransformParametersType & parameters) const override; 134 135 /** Get the derivatives of the match measure. */ 136 void GetDerivative(const TransformParametersType & parameters, 137 DerivativeType & derivative) const override; 138 139 /** Get value and derivatives for multiple valued optimizers. */ 140 void GetValueAndDerivative(const TransformParametersType & parameters, 141 MeasureType & Value, 142 DerivativeType & Derivative) const override; 143 144 /** Set the lower bounds of the intensities to be considered for computing 145 * the histogram. This option allows to focus the computation of the Metric in 146 * a particular range of intensities that correspond to features of interest. */ 147 void SetLowerBound(const MeasurementVectorType & bound); 148 149 /** Returns the current state of m_LowerBound. */ 150 const MeasurementVectorType & GetLowerBound() const; 151 152 /** Set the upper bounds of the intensities to be considered for computing 153 * the histogram. This option allows to focus the computation of the Metric in 154 * a particular range of intensities that correspond to features of interest. */ 155 void SetUpperBound(const MeasurementVectorType & bound); 156 157 /** Returns the current state of m_UpperBound. */ 158 const MeasurementVectorType & GetUpperBound() const; 159 160 protected: 161 /** Constructor is protected to ensure that \c New() function is used to 162 create instances. */ 163 HistogramImageToImageMetric(); 164 ~HistogramImageToImageMetric() override = default; 165 166 /** The histogram size. */ 167 HistogramSizeType m_HistogramSize; 168 /** The lower bound for samples in the histogram. */ 169 mutable MeasurementVectorType m_LowerBound; 170 /** The upper bound for samples in the histogram. */ 171 mutable MeasurementVectorType m_UpperBound; 172 /** The increase in the upper bound. */ 173 double m_UpperBoundIncreaseFactor; 174 175 /** Boolean flag to indicate whether the user supplied lower bounds or 176 * whether they should be computed from the min of image intensities */ 177 bool m_LowerBoundSetByUser; 178 179 /** Boolean flag to indicate whether the user supplied upper bounds or 180 * whether they should be computed from the max of image intensities */ 181 bool m_UpperBoundSetByUser; 182 183 /** Computes the joint histogram from the transformation parameters 184 passed to the function. */ 185 void ComputeHistogram(const TransformParametersType & parameters, 186 HistogramType & histogram) const; 187 188 /** Computes the joint histogram from the transformation parameters 189 passed to the function. */ 190 void ComputeHistogram(const TransformParametersType & parameters, 191 unsigned int parameter, 192 double step, 193 HistogramType & histogram) const; 194 195 /** Copies a histogram. */ 196 void CopyHistogram(HistogramType & target, HistogramType & source) const; 197 198 /** Evaluates the similarity measure using the given histogram. All 199 subclasses must reimplement this method. */ 200 virtual MeasureType EvaluateMeasure(HistogramType & histogram) const = 0; 201 202 /** PrintSelf function */ 203 void PrintSelf(std::ostream & os, Indent indent) const override; 204 205 private: 206 /** The padding value. */ 207 FixedImagePixelType m_PaddingValue; 208 209 /** True if those pixels in the fixed image with the same value as the 210 padding value should be ignored when calculating the similarity 211 measure. */ 212 bool m_UsePaddingValue; 213 214 /** The step length used to calculate the derivative. */ 215 double m_DerivativeStepLength; 216 217 /** The derivative step length scales. */ 218 ScalesType m_DerivativeStepLengthScales; 219 220 /** Pointer to the joint histogram. This is updated during every call to 221 * GetValue() */ 222 HistogramPointer m_Histogram; 223 }; 224 } // end namespace itk 225 226 #ifndef ITK_MANUAL_INSTANTIATION 227 #include "itkHistogramImageToImageMetric.hxx" 228 #endif 229 230 #endif // itkHistogramImageToImageMetric_h 231