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itkWatershedSegmenter.txx
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itkWatershedSegmenter.txx
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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkWatershedSegmenter.txx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkWatershedSegmenter_txx
#define __itkWatershedSegmenter_txx
#include "itkNeighborhoodAlgorithm.h"
#include "itkImageRegionIterator.h"
#include "itkConstNeighborhoodIterator.h"
#include "itkNeighborhoodIterator.h"
#include <stack>
#include <list>
namespace itk
{
namespace watershed
{
template <class TInputImage>
unsigned long Segmenter<TInputImage>::NULL_LABEL = 0;
template <class TInputImage>
short Segmenter<TInputImage>::NULL_FLOW = -1;
/*
----------------------------------------------------------------------------
Algorithm methods
----------------------------------------------------------------------------
*/
template <class TInputImage>
Segmenter<TInputImage>::~Segmenter()
{
if (m_Connectivity.index != 0)
{
delete[] m_Connectivity.index;
}
if (m_Connectivity.direction !=0 )
{
delete[] m_Connectivity.direction;
}
}
template <class TInputImage>
void Segmenter<TInputImage>::GenerateData()
{
//
// Allocate all the necessary temporary data structures and variables that
// will be used in this algorithm. Also re-initialize some temporary data
// structures that may have been used in previous updates of this filter.
//
unsigned int i;
this->UpdateProgress(0.0);
if (m_DoBoundaryAnalysis == false)
{
this->GetSegmentTable()->Clear();
this->SetCurrentLabel(1);
}
flat_region_table_t flatRegions;
typename InputImageType::Pointer input = this->GetInputImage();
typename OutputImageType::Pointer output = this->GetOutputImage();
typename BoundaryType::Pointer boundary = this->GetBoundary();
// ------------------------------------------------------------------------
//
// HERE ARE THE ASSUMPTIONS ABOUT REGION SIZES FOR NOW. WHEN THE PIPELINE
// FULLY SUPPORTS STREAMING, THESE WILL NEED TO BE CHANGED ACCORDINGLY.
//
// 1) All region sizes are equivalent. There is no distinction among
// regions. The region size is assumed to be padded one pixel out along each
// chunk face unless that face touches an actual data set boundary.
//
// 2) The ivar m_LargestPossibleRegion represents the actual size of the data
// set. This has to be set by the user since the pipeline sometimes clobbers
// the actual LargestPossibleRegion (?).
//
// -------------------------------------------------------------------------
//
// Generate the "face" regions A that constitute our shared boundary with
// another chunk. Also determine which face regions B lie on a the true
// dataset boundary. The faces corresponding to B will need to be padded
// out a pixel when we threshold so that we can construct the retaining wall
// along those faces.
//
ImageRegionType regionToProcess = output->GetRequestedRegion();
ImageRegionType largestPossibleRegion = this->GetLargestPossibleRegion();
ImageRegionType thresholdImageRegion = regionToProcess;
ImageRegionType thresholdLargestPossibleRegion
= this->GetLargestPossibleRegion();
// First we have to find the boundaries and adjust the threshold image size
typename ImageRegionType::IndexType tidx= thresholdImageRegion.GetIndex();
typename ImageRegionType::SizeType tsz = thresholdImageRegion.GetSize();
typename ImageRegionType::IndexType tlidx= thresholdLargestPossibleRegion.GetIndex();
typename ImageRegionType::SizeType tlsz = thresholdLargestPossibleRegion.GetSize();
for (i = 0; i < ImageDimension; ++i)
{
ImageRegionType reg;
typename ImageRegionType::IndexType idx = regionToProcess.GetIndex();
typename ImageRegionType::SizeType sz = regionToProcess.GetSize();
// Set LOW face
idx[i] = regionToProcess.GetIndex()[i];
sz[i] = 1;
reg.SetSize(sz);
reg.SetIndex(idx);
if (reg.GetIndex()[i] == largestPossibleRegion.GetIndex()[i])
{
// This is facing a true data set boundary
tsz[i] += 1; // we need to pad our threshold image on this face
tidx[i] -=1;
tlsz[i] += 1; // we need to pad our threshold image on this face
tlidx[i] -=1;
boundary->SetValid(false, i, 0);
}
else
{
// This is an overlap with another data chunk in the data set
// Mark this boundary face as valid.
boundary->SetValid(true, i, 0);
}
// Set HIGH face
idx[i]
= (regionToProcess.GetIndex()[i]+regionToProcess.GetSize()[i]) - 1;
reg.SetSize(sz);
reg.SetIndex(idx);
if ( (reg.GetIndex()[i] + reg.GetSize()[i])
== (largestPossibleRegion.GetIndex()[i]
+ largestPossibleRegion.GetSize()[i]) )
{
// This is facing a true data set boundary
tsz[i] +=1; // we need to pad our threshold image on this face
tlsz[i] +=1; // we need to pad our threshold image on this face
boundary->SetValid(false, i, 1);
}
else
{
// This is an overlap with another data chunk in the data set
// Mark this face as valid in the boundary.
boundary->SetValid(true, i, 1);
}
}
thresholdImageRegion.SetSize(tsz);
thresholdImageRegion.SetIndex(tidx);
thresholdLargestPossibleRegion.SetSize(tlsz);
thresholdLargestPossibleRegion.SetIndex(tlidx);
// Now create and allocate the threshold image. We need a single pixel
// border around the NxM region we are segmenting. This means that for faces
// that have no overlap into another chunk, we have to pad the image.
typename InputImageType::Pointer thresholdImage = InputImageType::New();
thresholdImage->SetLargestPossibleRegion(thresholdLargestPossibleRegion);
thresholdImage->SetBufferedRegion(thresholdImageRegion);
thresholdImage->SetRequestedRegion(thresholdImageRegion);
thresholdImage->Allocate();
// Now threshold the image. First we calculate the dynamic range of
// the input. Then, the threshold operation clamps the lower
// intensity values at the prescribed threshold. If the data is
// integral, then any intensity at NumericTraits<>::max() is reduced
// by one intensity value. This allows the watershed algorithm to
// build a barrier around the image with values above the maximum
// intensity value which trivially stop the steepest descent search
// for local minima without requiring expensive boundary conditions.
//
//
InputPixelType minimum, maximum;
Self::MinMax(input, regionToProcess, minimum, maximum);
// cap the maximum in the image so that we can always define a pixel
// value that is one greater than the maximum value in the image.
if (NumericTraits<InputPixelType>::is_integer
&& maximum == NumericTraits<InputPixelType>::max())
{
maximum -= NumericTraits<InputPixelType>::One;
}
// threshold the image.
Self::Threshold(thresholdImage, input, regionToProcess, regionToProcess,
static_cast<InputPixelType>((m_Threshold * (maximum - minimum)) + minimum));
//
// Redefine the regionToProcess in terms of the threshold image. The region
// to process represents all the pixels contained within the 1 pixel padded
// boundary of the threshold image.
//
typename ImageRegionType::SizeType irsz;
typename ImageRegionType::IndexType iridx;
for (i = 0; i < ImageDimension; ++i)
{
irsz[i] = thresholdImageRegion.GetSize()[i] - 2;
iridx[i] = thresholdImageRegion.GetIndex()[i] + 1;
}
regionToProcess.SetIndex(iridx);
regionToProcess.SetSize(irsz);
//
// Initialize the connectivity information that will be used by the
// segmentation algorithm.
//
this->GenerateConnectivity();
//
// Store the regionToProcess in the RequestedRegion of the threshold image.
// We are now completely done with the input image. The input image memory
// can be released at this point if need be.
//
thresholdImage->SetRequestedRegion(regionToProcess);
this->ReleaseInputs();
//
// At this point we are ready to define the output
// buffer and allocate memory for the output image.
//
output->SetBufferedRegion(thresholdImage->GetBufferedRegion());
output->Allocate();
Self::SetOutputImageValues(output, output->GetBufferedRegion(), Self::NULL_LABEL);
//
// Now we can create appropriate boundary regions for analyzing the
// flow at the boundaries from the requested region of the threshold
// image.
//
typename BoundaryType::IndexType b_idx;
ImageRegionType reg_b;
typename ImageRegionType::IndexType idx_b;
typename ImageRegionType::SizeType sz_b;
for (b_idx.first = 0; b_idx.first < ImageDimension; ++b_idx.first)
for (b_idx.second = 0; b_idx.second < 2; ++b_idx.second)
{
if (boundary->GetValid(b_idx) == false) continue;
idx_b = thresholdImage->GetRequestedRegion().GetIndex();
sz_b = thresholdImage->GetRequestedRegion().GetSize();
if (b_idx.second == 1) // HIGH face must adjust start index
idx_b[b_idx.first] += sz_b[b_idx.first] - 1;
sz_b[b_idx.first] = 1;
reg_b.SetIndex(idx_b);
reg_b.SetSize(sz_b);
boundary->GetFace(b_idx)->SetLargestPossibleRegion(reg_b);
boundary->GetFace(b_idx)->SetRequestedRegion(reg_b);
boundary->GetFace(b_idx)->SetBufferedRegion(reg_b);
boundary->GetFace(b_idx)->Allocate();
}
this->UpdateProgress(0.1);
//
// Analyze the flow at the boundaries. This method labels all the boundary
// pixels that flow out of this chunk (either through gradient descent or
// flat-region connectivity) and constructs the appropriate Boundary
// data structures.
//
if (m_DoBoundaryAnalysis == true)
{
this->InitializeBoundary();
this->AnalyzeBoundaryFlow(thresholdImage, flatRegions, maximum +
NumericTraits<InputPixelType>::One);
}
this->UpdateProgress(0.2);
//
// Build a ``retaining wall'' around the image so that gradient descent
// analysis can be done without worrying about boundaries.
//
// All overlap boundary information will be overwritten, but is no longer
// needed now.
//
this->BuildRetainingWall( thresholdImage,
thresholdImage->GetBufferedRegion(),
maximum + NumericTraits<InputPixelType>::One );
//
// Label all the local minima pixels in the image. This function also
// labels flat regions, defined as regions where connected pixels all have
// the same value.
//
this->LabelMinima(thresholdImage, thresholdImage->GetRequestedRegion(),
flatRegions, maximum + NumericTraits<InputPixelType>::One);
this->UpdateProgress(0.3);
this->GradientDescent(thresholdImage, thresholdImage->GetRequestedRegion());
this->UpdateProgress(0.4);
this->DescendFlatRegions(flatRegions, thresholdImage->GetRequestedRegion());
this->UpdateProgress(0.5);
this->UpdateSegmentTable(thresholdImage, thresholdImage->GetRequestedRegion());
this->UpdateProgress(0.6);
if (m_DoBoundaryAnalysis == true)
{ this->CollectBoundaryInformation(flatRegions); }
this->UpdateProgress(0.7);
if (m_SortEdgeLists == true)
{ this->GetSegmentTable()->SortEdgeLists(); }
this->UpdateProgress(0.8);
this->GetSegmentTable()->SetMaximumDepth(maximum - minimum);
this->UpdateProgress(1.0);
}
template <class TInputImage>
void Segmenter<TInputImage>
::CollectBoundaryInformation(flat_region_table_t &flatRegions)
{
typename OutputImageType::Pointer output = this->GetOutputImage();
typename BoundaryType::Pointer boundary = this->GetBoundary();
ImageRegionIterator<ITK_TYPENAME BoundaryType::face_t> faceIt;
ImageRegionIterator<OutputImageType> labelIt;
typename BoundaryType::face_t::Pointer face;
typedef typename BoundaryType::flat_hash_t flats_t;
typename BoundaryType::flat_hash_t *flats;
typename BoundaryType::flat_hash_t::iterator flats_it;
typename BoundaryType::flat_region_t flr;
typename flat_region_table_t::iterator flrt_it;
typename BoundaryType::IndexType idx;
ImageRegionType region;
for (idx.first = 0; idx.first < ImageDimension; (idx.first)++)
for (idx.second = 0; idx.second < 2; (idx.second)++)
{
if (boundary->GetValid(idx) == false) continue;
face = boundary->GetFace(idx);
flats = boundary->GetFlatHash(idx);
region = face->GetRequestedRegion();
// Grab all the labels of the boundary pixels.
faceIt = ImageRegionIterator<ITK_TYPENAME BoundaryType::face_t> (face,
region);
labelIt = ImageRegionIterator<OutputImageType> (output, region);
faceIt = faceIt.Begin();
labelIt = labelIt.Begin();
while (! faceIt.IsAtEnd() )
{
faceIt.Value().label = labelIt.Get();
// Is this a flat region that flows out?
flrt_it = flatRegions.find(labelIt.Get());
if ( faceIt.Get().flow != NULL_FLOW
&& flrt_it != flatRegions.end() )
{
// Have we already entered this
// flat region into the boundary?
flats_it = flats->find(labelIt.Get());
if (flats_it == flats->end()) // NO
{
flr.bounds_min = (*flrt_it).second.bounds_min;
flr.min_label = *((*flrt_it).second.min_label_ptr);
flr.value = (*flrt_it).second.value;
flr.offset_list.push_back(
face->ComputeOffset(faceIt.GetIndex()));
flats->insert(
BoundaryFlatHashValueType(labelIt.Get(), flr));
flr.offset_list.clear();
}
else // YES
{
(*flats_it).second.offset_list.push_back(face->ComputeOffset(faceIt.GetIndex()));
}
}
++faceIt;
++labelIt;
}
}
}
template <class TInputImage>
void Segmenter<TInputImage>
::InitializeBoundary()
{
ImageRegionIterator<ITK_TYPENAME BoundaryType::face_t> faceIt;
typename BoundaryType::face_t::Pointer face;
typename BoundaryType::face_pixel_t fps;
BoundaryIndexType idx;
fps.flow = NULL_FLOW;
fps.label = NULL_LABEL;
for (idx.first = 0; idx.first < ImageDimension; ++(idx.first))
for (idx.second = 0; idx.second < 2; ++(idx.second))
{
if (this->GetBoundary()->GetValid(idx) == false) continue;
this->GetBoundary()->GetFlatHash(idx)->clear();
face = this->GetBoundary()->GetFace(idx);
faceIt = ImageRegionIterator<ITK_TYPENAME BoundaryType::face_t>
(face, face->GetBufferedRegion());
for (faceIt = faceIt.Begin(); ! faceIt.IsAtEnd(); ++faceIt)
faceIt.Set(fps);
}
}
template <class TInputImage>
void Segmenter<TInputImage>
::AnalyzeBoundaryFlow(InputImageTypePointer thresholdImage,
flat_region_table_t &flatRegions,
InputPixelType max)
{
//
// NOTE: For ease of initial implementation, this method does
// not support arbitrary connectivity across boundaries (yet). 10-8-01 jc
//
unsigned int nCenter, i, nPos, cPos;
bool isSteepest;
ConstNeighborhoodIterator<InputImageType> searchIt;
NeighborhoodIterator<OutputImageType> labelIt;
ImageRegionIterator<ITK_TYPENAME BoundaryType::face_t> faceIt;
BoundaryIndexType idx;
ImageRegionType region;
typename ConstNeighborhoodIterator<InputImageType>::RadiusType rad;
typename BoundaryType::face_pixel_t fps;
flat_region_t tempFlatRegion;
typename OutputImageType::Pointer output = this->GetOutputImage();
typename BoundaryType::Pointer boundary = this->GetBoundary();
for (i = 0; i < ImageDimension; ++i) rad[i] = 1;
fps.label = NULL_LABEL;
EquivalencyTable::Pointer eqTable = EquivalencyTable::New();
// Process each boundary region.
for (idx.first = 0; idx.first < ImageDimension; ++(idx.first))
{
for (idx.second = 0; idx.second < 2; ++(idx.second))
{
// Skip irrelevant boundaries
if (boundary->GetValid(idx) == false) continue;
typename BoundaryType::face_t::Pointer face = boundary->GetFace(idx);
region = face->GetRequestedRegion();
searchIt
= ConstNeighborhoodIterator<InputImageType> (rad, thresholdImage, region);
labelIt = NeighborhoodIterator<OutputImageType> (rad, output, region);
faceIt = ImageRegionIterator<ITK_TYPENAME BoundaryType::face_t> (face, region);
nCenter = searchIt.Size() / 2;
searchIt.GoToBegin();
labelIt.GoToBegin();
if ((idx).second == 0)
{
// Low face
cPos = m_Connectivity.index[(idx).first];
}
else
{
// High face
cPos = m_Connectivity.index[(ImageDimension - 1)
+ (ImageDimension - (idx).first)];
}
while ( ! searchIt.IsAtEnd() )
{
// Is this a flat connection?
if ( searchIt.GetPixel(nCenter) == searchIt.GetPixel(cPos) )
{
// Fill in the boundary flow information.
// Labels will be collected later.
fps.flow = static_cast<short>(cPos);
faceIt.Set(fps);
// Are we touching flat regions
// that have already been labeled?
bool _labeled = false;
bool _connected = false;
for ( i=0; i <m_Connectivity.size; i++)
{
nPos = m_Connectivity.index[i];
if ( searchIt.GetPixel(nCenter) == searchIt.GetPixel(nPos)
&& labelIt.GetPixel(nPos) != Self::NULL_LABEL
&& labelIt.GetPixel(nPos) != labelIt.GetPixel(nCenter)
)
{
_connected = true;
if (_labeled == false)
{
labelIt.SetPixel(nCenter,
labelIt.GetPixel(nPos));
_labeled = true;
}
else
{
eqTable->Add(labelIt.GetPixel(nCenter), labelIt.GetPixel(nPos));
}
}
}
if (_connected == false ) // Add a new flat region.
{
labelIt.SetPixel(nCenter, m_CurrentLabel);
// Add a flat region to the (global) flat region table
tempFlatRegion.bounds_min = max;
tempFlatRegion.min_label_ptr = output->GetBufferPointer() +
output->ComputeOffset(labelIt.GetIndex());
tempFlatRegion.value = searchIt.GetPixel(nCenter);
tempFlatRegion.is_on_boundary= true;
flatRegions[m_CurrentLabel] = tempFlatRegion;
m_CurrentLabel++;
}
}
else // Is cPos the path of steepest descent?
{
if ( searchIt.GetPixel(cPos) < searchIt.GetPixel(nCenter) )
{
isSteepest = true;
for (i = 0; i < m_Connectivity.size; i++)
{
nPos = m_Connectivity.index[i];
if (searchIt.GetPixel(nPos) < searchIt.GetPixel(cPos))
{
isSteepest = false;
break;
}
}
}
else isSteepest = false;
if (isSteepest == true)
{
// Label this pixel. It will be safely treated as a local
// minimum by the rest of the segmentation algorithm.
labelIt.SetPixel(nCenter, m_CurrentLabel);
// Add the connectivity information
// to the boundary data structure.
fps.flow = static_cast<short>(cPos);
faceIt.Set(fps);
// Since we've labeled this pixel, we need to check to
// make sure this is not also a flat region. If it is,
// then it must be entered into the flat region table
// or we could have problems later on.
for (i = 0; i < m_Connectivity.size; i++)
{
nPos = m_Connectivity.index[i];
if ( searchIt.GetPixel(nPos) ==
searchIt.GetPixel(nCenter) )
{
tempFlatRegion.bounds_min = max;
tempFlatRegion.min_label_ptr =
output->GetBufferPointer() +
output->ComputeOffset(labelIt.GetIndex());
tempFlatRegion.value =
searchIt.GetPixel(nCenter);
tempFlatRegion.is_on_boundary = false;
flatRegions[m_CurrentLabel] = tempFlatRegion;
break;
}
}
m_CurrentLabel++;
}
}
++searchIt;
++labelIt;
++faceIt;
}
}
}
eqTable->Flatten();
// Now relabel any equivalent regions in the boundaries.
for (idx.first = 0; idx.first < ImageDimension; ++(idx.first))
{
for (idx.second = 0; idx.second < 2; ++(idx.second))
{
// Skip irrelevant boundaries
if (boundary->GetValid(idx) == false) continue;
typename BoundaryType::face_t::Pointer face = boundary->GetFace(idx);
region = face->GetRequestedRegion();
Self::RelabelImage(output, region, eqTable);
}
}
// Merge the flat regions in the table
Self::MergeFlatRegions(flatRegions, eqTable);
}
template <class TInputImage>
void Segmenter<TInputImage>
::GenerateConnectivity()
{
unsigned int i, j, nSize, nCenter, stride;
int d;
//
// Creates city-block style connectivity. 4-Neighbors in 2D. 6-Neighbors in
// 3D, etc... Order of creation MUST be lowest index to highest index in the
// neighborhood. I.e. for 4 connectivity,
//
// * 1 *
// 2 * 3
// * 4 *
//
// Algorithms assume this order to the connectivity.
//
typename ConstNeighborhoodIterator<InputImageType>::RadiusType rad;
for (i = 0; i < ImageDimension; ++i) rad[i] = 1;
ConstNeighborhoodIterator<InputImageType> it(rad, this->GetInputImage(),
this->GetInputImage()->GetRequestedRegion());
nSize = it.Size();
nCenter = nSize >> 1;
for (i =0; i < m_Connectivity.size; i++) // initialize move list
{
for (j =0; j < ImageDimension; j++) m_Connectivity.direction[i][j] = 0;
}
i = 0;
for (d = ImageDimension-1; d >=0; d--)
{
stride = it.GetStride(d);
m_Connectivity.index[i] = nCenter - stride;
m_Connectivity.direction[i][d] = -1;
i++;
}
for (d = 0; d < static_cast<int>(ImageDimension); d++)
{
stride = it.GetStride(d);
m_Connectivity.index[i] = nCenter + stride;
m_Connectivity.direction[i][d] = 1;
i++;
}
}
template <class TInputImage>
void Segmenter<TInputImage>
::LabelMinima(InputImageTypePointer img, ImageRegionType region,
typename Self::flat_region_table_t &flatRegions, InputPixelType Max)
{
unsigned int i, nSize, nCenter, nPos = 0;
bool foundSinglePixelMinimum, foundFlatRegion;
InputPixelType maxValue = Max;
flat_region_t tempFlatRegion;
typename flat_region_table_t::iterator flatPtr;
InputPixelType currentValue;
EquivalencyTable::Pointer equivalentLabels = EquivalencyTable::New();
typename OutputImageType::Pointer output = this->GetOutputImage();
// Set up the iterators.
typename ConstNeighborhoodIterator<InputImageType>::RadiusType rad;
for (i = 0; i < ImageDimension; ++i) rad[i] = 1;
ConstNeighborhoodIterator<InputImageType> searchIt(rad, img, region);
NeighborhoodIterator<OutputImageType> labelIt(rad, output, region);
nSize = searchIt.Size();
nCenter = nSize >> 1;
// Sweep through the images. Label all local minima
// and record information for all the flat regions.
for (searchIt.GoToBegin(), labelIt.GoToBegin();
! searchIt.IsAtEnd(); ++searchIt, ++labelIt)
{
foundSinglePixelMinimum = true;
foundFlatRegion = false;
// If this pixel has been labeled already,
// skip directly to the next iteration.
if ( labelIt.GetPixel(nCenter) != Self::NULL_LABEL ) continue;
// Compare current pixel value with its neighbors.
currentValue = searchIt.GetPixel(nCenter);
for (i = 0; i < m_Connectivity.size; ++i)
{
nPos = m_Connectivity.index[i];
if ( currentValue == searchIt.GetPixel(nPos) )
{
foundFlatRegion = true;
break;
}
else if ( currentValue > searchIt.GetPixel(nPos) )
{
foundSinglePixelMinimum = false;
}
}
if (foundFlatRegion)
{
if ( labelIt.GetPixel(nPos) != Self::NULL_LABEL )// If the flat region is already
{ // labeled, label this to match.
labelIt.SetPixel(nCenter, labelIt.GetPixel(nPos));
}
else // Add a new flat region to the table.
{ // Initialize its contents.
labelIt.SetPixel(nCenter, m_CurrentLabel);
nPos = m_Connectivity.index[0];
tempFlatRegion.bounds_min = maxValue;
tempFlatRegion.min_label_ptr = labelIt[nPos];
tempFlatRegion.value = currentValue;
flatRegions[m_CurrentLabel] = tempFlatRegion;
m_CurrentLabel = m_CurrentLabel + 1;
}
// While we're at it, check to see if we have just linked two flat
// regions with the same height value. Save that info for later.
for ( i++; i <m_Connectivity.size; ++i)
{
nPos = m_Connectivity.index[i];
if ( searchIt.GetPixel(nCenter) == searchIt.GetPixel(nPos)
&& labelIt.GetPixel(nPos)!=Self::NULL_LABEL
&& labelIt.GetPixel(nPos)!=labelIt.GetPixel(nCenter)
)
{
equivalentLabels->Add(labelIt.GetPixel(nCenter),
labelIt.GetPixel(nPos));
}
}
}
else if (foundSinglePixelMinimum)
{
labelIt.SetPixel(nCenter, m_CurrentLabel);
m_CurrentLabel = m_CurrentLabel + 1;
}
}
// Merge the flat regions that we identified as connected components.
Self::MergeFlatRegions(flatRegions, equivalentLabels);
// Relabel the image with the merged regions.
Self::RelabelImage(output, region, equivalentLabels);
equivalentLabels->Clear();
// Now make another pass to establish the
// boundary values for the flat regions.
for (searchIt.GoToBegin(), labelIt.GoToBegin();
! searchIt.IsAtEnd(); ++searchIt, ++labelIt)
{
flatPtr = flatRegions.find( labelIt.GetPixel(nCenter) );
if ( flatPtr != flatRegions.end() ) // If we are in a flat region
{ // Search the connectivity neighborhood
// for lesser boundary pixels.
for (i = 0; i < m_Connectivity.size; ++i)
{
nPos = m_Connectivity.index[i];
if ( labelIt.GetPixel(nPos) != labelIt.GetPixel(nCenter) &&
searchIt.GetPixel(nPos) < (*flatPtr).second.bounds_min )
{ // If this is a boundary pixel && has a lesser value than
// the currently recorded value...
(*flatPtr).second.bounds_min = searchIt.GetPixel(nPos);
(*flatPtr).second.min_label_ptr = labelIt[nPos];
}
if ( searchIt.GetPixel(nCenter) == searchIt.GetPixel(nPos) )
{
if ( labelIt.GetPixel(nPos) != NULL_LABEL )
{
// Pick up any equivalencies we missed before.
equivalentLabels->Add(labelIt.GetPixel(nCenter),
labelIt.GetPixel(nPos));
}
// If the following is encountered, it means that there is a
// logic flaw in the first pass of this algorithm where flat
// regions are initially detected and linked.
#ifndef NDEBUG
else itkDebugMacro("An unexpected but non-fatal error has occurred.");
#endif
}
}
}
}
// Merge the flat regions that we identified as connected components.
Self::MergeFlatRegions(flatRegions, equivalentLabels);
// Relabel the image with the merged regions.
Self::RelabelImage(output, region, equivalentLabels);
}
template <class TInputImage>
void Segmenter<TInputImage>
::GradientDescent(InputImageTypePointer img,
ImageRegionType region)
{
typename OutputImageType::Pointer output = this->GetOutputImage();
InputPixelType minVal;
unsigned int i, nPos;
typename InputImageType::OffsetType moveIndex;
unsigned long newLabel;
std::stack< unsigned long * > updateStack;
//
// Set up our iterators.
//
typename ConstNeighborhoodIterator<InputImageType>::RadiusType rad;
typename NeighborhoodIterator<OutputImageType>::RadiusType zeroRad;
for (i = 0; i < ImageDimension; ++i)
{
rad[i] = 1;
zeroRad[i] = 0;
}
ConstNeighborhoodIterator<InputImageType>
valueIt(rad, img, region);
NeighborhoodIterator<OutputImageType>
labelIt(zeroRad, output, region);
ImageRegionIterator<OutputImageType> it(output, region);
//
// Sweep through the image and trace all unlabeled
// pixels to a labeled region
//
for (it = it.Begin(); ! it.IsAtEnd(); ++it)
{
if ( it.Get() == NULL_LABEL )
{
valueIt.SetLocation(it.GetIndex());
labelIt.SetLocation(it.GetIndex());
newLabel = NULL_LABEL; // Follow the path of steep-
while( newLabel == NULL_LABEL ) // est descent until a label
{ // is found.
updateStack.push(labelIt.GetCenterPointer());
minVal = valueIt.GetPixel(m_Connectivity.index[0]);
moveIndex = m_Connectivity.direction[0];
for (unsigned int ii = 1; ii < m_Connectivity.size; ++ii)
{
nPos = m_Connectivity.index[ii];
if ( valueIt.GetPixel(nPos) < minVal)
{
minVal = valueIt.GetPixel(nPos);
moveIndex = m_Connectivity.direction[ii];
}
}
valueIt += moveIndex;
labelIt += moveIndex;
newLabel = labelIt.GetPixel(0);
}
while( ! updateStack.empty() ) // Update all the pixels we've traversed
{
*(updateStack.top()) = newLabel;
updateStack.pop();
}
}
}
}
template <class TInputImage>
void Segmenter<TInputImage>
::DescendFlatRegions(flat_region_table_t &flatRegionTable,
ImageRegionType imageRegion)
{
typename OutputImageType::Pointer output = this->GetOutputImage();
// Assumes all pixels are labeled in the image. Steps through the flat
// regions and equates each one with the label at its lowest boundary
// point. Flat basins are preserved as their own regions. The output image is
// relabeled to reflect these equivalencies.
EquivalencyTable::Pointer equivalentLabels = EquivalencyTable::New();
for (typename flat_region_table_t::const_iterator region = flatRegionTable.begin();
region != flatRegionTable.end(); ++region)
{
if ( ((*region).second.bounds_min < (*region).second.value)
&& (! (*region).second.is_on_boundary) )
{
equivalentLabels->Add((*region).first, *((*region).second.min_label_ptr));
}
}
equivalentLabels->Flatten();
Self::RelabelImage(output, imageRegion, equivalentLabels);
}
template <class TInputImage>
void Segmenter<TInputImage>
::UpdateSegmentTable(InputImageTypePointer input, ImageRegionType region)
{
edge_table_hash_t edgeHash;
edge_table_t tempEdgeTable;
typename edge_table_hash_t::iterator edge_table_entry_ptr;
typename edge_table_t::iterator edge_ptr;
unsigned int i, nPos;
typename NeighborhoodIterator<OutputImageType>::RadiusType hoodRadius;
typename SegmentTableType::segment_t *segment_ptr;
typename SegmentTableType::segment_t temp_segment;
unsigned long segment_label;
InputPixelType lowest_edge;
// Grab the data we need.
typename OutputImageType::Pointer output = this->GetOutputImage();
typename SegmentTableType::Pointer segments = this->GetSegmentTable();
// Set up some iterators.
for (i = 0; i < ImageDimension; i++) hoodRadius[i] = 1;
ConstNeighborhoodIterator<InputImageType> searchIt(hoodRadius,input,region);
NeighborhoodIterator<OutputImageType> labelIt(hoodRadius, output, region);
unsigned long hoodCenter = searchIt.Size() >> 1;
for (searchIt.GoToBegin(), labelIt.GoToBegin(); ! searchIt.IsAtEnd();
++searchIt, ++labelIt)
{
segment_label = labelIt.GetPixel(hoodCenter);
// Find the segment corresponding to this label
// and update its minimum value if necessary.
segment_ptr = segments->Lookup(segment_label);
edge_table_entry_ptr = edgeHash.find(segment_label);
if (segment_ptr == 0) // This segment not yet identified.
{ // So add it to the table.
temp_segment.min = searchIt.GetPixel(hoodCenter);
segments->Add(segment_label, temp_segment);
typedef typename edge_table_hash_t::value_type ValueType;
edgeHash.insert(ValueType(segment_label,
tempEdgeTable) );
edge_table_entry_ptr = edgeHash.find(segment_label);
}
else if (searchIt.GetPixel(hoodCenter) < segment_ptr->min)
{
segment_ptr->min = searchIt.GetPixel(hoodCenter);
}
// Look up each neighboring segment in this segment's edge table.
// If an edge exists, compare (and reset) the minimum edge value.
// Note that edges are located *between* two adjacent pixels and
// the value is taken to be the maximum of the two adjacent pixel
// values.
for (i = 0; i < m_Connectivity.size; ++i)
{
nPos = m_Connectivity.index[i];
if (labelIt.GetPixel(nPos) != segment_label
&& labelIt.GetPixel(nPos) != NULL_LABEL)
{
if (searchIt.GetPixel(nPos) < searchIt.GetPixel(hoodCenter))
lowest_edge = searchIt.GetPixel(hoodCenter); // We want the
else lowest_edge = searchIt.GetPixel(nPos); // max of the
// adjacent pixels
edge_ptr = (*edge_table_entry_ptr).second.find(labelIt.GetPixel(nPos));
if ( edge_ptr == (*edge_table_entry_ptr).second.end() )
{ // This edge has not been identified yet.
typedef typename edge_table_t::value_type ValueType;
(*edge_table_entry_ptr).second.insert(
ValueType(labelIt.GetPixel(nPos), lowest_edge) );
}
else if (lowest_edge < (*edge_ptr).second)
{
(*edge_ptr).second = lowest_edge;
}
}
}
}