/*========================================================================= * * 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 itkVectorLinearInterpolateNearestNeighborExtrapolateImageFunction_hxx #define itkVectorLinearInterpolateNearestNeighborExtrapolateImageFunction_hxx #include "itkMath.h" namespace itk { /** * Define the number of neighbors */ template const unsigned int VectorLinearInterpolateNearestNeighborExtrapolateImageFunction::m_Neighbors = 1 << TInputImage::ImageDimension; template auto VectorLinearInterpolateNearestNeighborExtrapolateImageFunction::EvaluateAtContinuousIndex( const ContinuousIndexType & index) const -> OutputType { unsigned int dim; // index over dimension // // Compute base index = closest index below point // Compute distance from point to base index // IndexType baseIndex; IndexType neighIndex; double distance[ImageDimension]; for (dim = 0; dim < ImageDimension; ++dim) { baseIndex[dim] = Math::Floor(index[dim]); if (baseIndex[dim] >= this->m_StartIndex[dim]) { if (baseIndex[dim] < this->m_EndIndex[dim]) { distance[dim] = index[dim] - static_cast(baseIndex[dim]); } else { baseIndex[dim] = this->m_EndIndex[dim]; distance[dim] = 0.0; } } else { baseIndex[dim] = this->m_StartIndex[dim]; distance[dim] = 0.0; } } // // Interpolated value is the weight some of each of the surrounding // neighbors. The weight for each neighbour is the fraction overlap // of the neighbor pixel with respect to a pixel centered on point. // OutputType output; NumericTraits::SetLength(output, this->GetInputImage()->GetNumberOfComponentsPerPixel()); output.Fill(0.0); RealType totalOverlap = 0.0; for (unsigned int counter = 0; counter < m_Neighbors; ++counter) { double overlap = 1.0; // fraction overlap unsigned int upper = counter; // each bit indicates upper/lower neighbour // get neighbor index and overlap fraction for (dim = 0; dim < ImageDimension; ++dim) { if (upper & 1) { neighIndex[dim] = baseIndex[dim] + 1; overlap *= distance[dim]; } else { neighIndex[dim] = baseIndex[dim]; overlap *= 1.0 - distance[dim]; } upper >>= 1; } // get neighbor value only if overlap is not zero if (overlap) { const PixelType input = this->GetInputImage()->GetPixel(neighIndex); for (unsigned int k = 0; k < this->GetInputImage()->GetNumberOfComponentsPerPixel(); ++k) { output[k] += overlap * static_cast(input[k]); } totalOverlap += overlap; } if (totalOverlap == 1.0) { // finished break; } } return (output); } /** * Evaluate at image index position */ template auto VectorLinearInterpolateNearestNeighborExtrapolateImageFunction::EvaluateAtIndex( const IndexType & index) const -> OutputType { // Find the index that is closest to the requested one // but that lies within the image IndexType insideIndex; for (unsigned int dim = 0; dim < ImageDimension; ++dim) { if (index[dim] >= this->m_StartIndex[dim]) { if (index[dim] < this->m_EndIndex[dim]) { insideIndex[dim] = index[dim]; } else { insideIndex[dim] = this->m_EndIndex[dim]; } } else { insideIndex[dim] = this->m_StartIndex[dim]; } } // Now call the superclass implementation of EvaluateAtIndex // since we have ensured that the index lies in the image region return this->Superclass::EvaluateAtIndex(insideIndex); } } // end namespace itk #endif