1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
|
/*=========================================================================
*
* 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 itkVectorLinearInterpolateImageFunction_hxx
#define itkVectorLinearInterpolateImageFunction_hxx
#include "itkMath.h"
#include <algorithm> // For min and max.
namespace itk
{
template <typename TInputImage, typename TCoordRep>
const unsigned long VectorLinearInterpolateImageFunction<TInputImage, TCoordRep>::m_Neighbors =
1 << TInputImage::ImageDimension;
template <typename TInputImage, typename TCoordRep>
auto
VectorLinearInterpolateImageFunction<TInputImage, TCoordRep>::EvaluateAtContinuousIndex(
const ContinuousIndexType & index) const -> OutputType
{
//
// Compute base index = closet index below point
// Compute distance from point to base index
//
IndexType baseIndex;
InternalComputationType distance[ImageDimension];
const TInputImage * const inputImgPtr = this->GetInputImage();
for (unsigned int dim = 0; dim < ImageDimension; ++dim)
{
baseIndex[dim] = Math::Floor<IndexValueType>(index[dim]);
distance[dim] = index[dim] - static_cast<InternalComputationType>(baseIndex[dim]);
}
/**
* Interpolated value is the weighted sum of each of the surrounding
* neighbors. The weight for each neighbor is the fraction overlap
* of the neighbor pixel with respect to a pixel centered on point.
*/
OutputType output;
output.Fill(0.0);
using ScalarRealType = typename NumericTraits<PixelType>::ScalarRealType;
ScalarRealType totalOverlap{};
for (unsigned int counter = 0; counter < m_Neighbors; ++counter)
{
InternalComputationType overlap = 1.0; // fraction overlap
unsigned int upper = counter; // each bit indicates upper/lower neighbour
IndexType neighIndex;
// get neighbor index and overlap fraction
for (unsigned int dim = 0; dim < ImageDimension; ++dim)
{
if (upper & 1)
{
neighIndex[dim] = baseIndex[dim] + 1;
// Take care of the case where the pixel is just
// in the outer upper boundary of the image grid.
neighIndex[dim] = std::min(neighIndex[dim], this->m_EndIndex[dim]);
overlap *= distance[dim];
}
else
{
neighIndex[dim] = baseIndex[dim];
// Take care of the case where the pixel is just
// in the outer lower boundary of the image grid.
neighIndex[dim] = std::max(neighIndex[dim], this->m_StartIndex[dim]);
overlap *= 1.0 - distance[dim];
}
upper >>= 1;
}
// get neighbor value only if overlap is not zero
if (overlap)
{
const PixelType & input = inputImgPtr->GetPixel(neighIndex);
for (unsigned int k = 0; k < Dimension; ++k)
{
output[k] += overlap * static_cast<InternalComputationType>(input[k]);
}
totalOverlap += overlap;
}
if (totalOverlap == 1.0)
{
// finished
break;
}
}
return (output);
}
} // end namespace itk
#endif
|
