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msegfastedge.cpp
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/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
* msegstd.cpp: MSEG Fast mode class with edge compensation *
* Version: 0.9.x *
* Last revised: 31/03/2010 *
* *
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
* MSEG algorithm by Angelos Tzotsos ([email protected]) *
* Remote Sensing Lab NTUA - GCpp March 2010 *
* *
* Copyright (C) Angelos Tzotsos <[email protected]> *
* *
* This program is free software: you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation, either version 2 of the License, or *
* (at your option) any later version. *
* *
* This program is distributed in the hope that it will be useful, *
* but WITHOUT ANY WARRANTY; without even the implied warranty of *
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the *
* GNU General Public License for more details. *
* *
* You should have received a copy of the GNU General Public License *
* along with this program. If not, see <http://www.gnu.org/licenses/>. *
* *
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
#include "msegfastedge.h"
int FastEdge_Mode::firstpass(Level& pass1, ERS_Image& Img, ERS_Image& ImgEdge, MSEG_Init& mseg, float level_ID, MSEG_Param& Param){
int mergecounter = 0;
int edgecounter = 0;
pass1.raster.reserve(Img.Lines*Img.Columns);
pass1.cycles = 1;
pass1.Lines = Img.Lines;
pass1.Columns = Img.Columns;
mseg.last_id = (Img.Lines*Img.Columns); //Set the first object id
//Let all the raster become -1
for (int i=0; i<(Img.Lines*Img.Columns); i++){
pass1.raster.push_back(-1);
//pass1.raster[i] = -1;//Solution 2, without reallocating memory into the vector
}
//Copy the id number
pass1.HierarchyID = level_ID;
//Copy segmentation parameters into new level
pass1.ScaleParameter = Param.Scale;
pass1.Color = Param.Color;
pass1.Compactness = Param.Compact;
pass1.Edge = Param.Edge;
//Declare a temporary object
Object tmp;
BoundaryLine tmpBoundaryLine;
PriorityObject tmp_priority_object;
pixel cur, up, down, right, left, best, best_up, best_down, best_right, best_left, best_best;
int cur_id, up_id, down_id, right_id, left_id, best_id, best_best_id;
int best_up_id, best_down_id, best_right_id, best_left_id;
int i, c, l, pri, sec, matches, pri_edge;
float best_h, up_h, down_h, left_h, right_h, best_up_h, best_down_h, best_right_h, best_left_h, best_best_h;
float std;
float cur_val, near_val;
//Check the SPE result number
if (mseg.StartingPoints.size() != Img.Macroblocks.size()){
cout << "Error in SPE result" << endl << "Quiting at first pass..." << endl;
exit(1);
}
int msize = Img.Macroblocks.size();
//For every macroblock
for(i=0;i<(Img.MacroLines * Img.MacroColumns);i++){
//Assume each pixel is an object and assign them false ids in order to use the priority_queue
//The pixel false id is the 1D index of the raster vector
pri = 1;//During first pass only primary is used.(inside macroblock)
sec = 1;
pri_edge = 1000000;
//Load the Starting Point
cur.line = mseg.StartingPoints[i].line;
cur.column = mseg.StartingPoints[i].column;
cur_id = D1(Img.Lines, Img.Columns, cur.line, cur.column) + 1;
//Check the boundary for the starting point
if ((cur.line<Img.Macroblocks[i].LineStart || cur.line>Img.Macroblocks[i].LineEnd)
||(cur.column<Img.Macroblocks[i].ColumnStart || cur.column>Img.Macroblocks[i].ColumnEnd)){
cout << "Starting point" << i << "out of bounds" << endl
<< "Quiting at first pass..." << endl;
exit(1);
}
//Push the first pixel to the priority_queue
tmp_priority_object.primary = pri;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = cur_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[cur_id - 1] = 0; //Flag that it is loaded into priority list
//Edge additions START
for(l=Img.Macroblocks[i].LineStart;l<=Img.Macroblocks[i].LineEnd;l++){
for(c=Img.Macroblocks[i].ColumnStart;c<=Img.Macroblocks[i].ColumnEnd;c++){
if(ImgEdge.Buffer(l, c, 1) == 255.0){
cur.line = l;
cur.column = c;
cur_id = D1(Img.Lines, Img.Columns, cur.line, cur.column) + 1;
//Load neigbors
up.line = cur.line - 1;
up.column = cur.column;
up_id = (up.line >= 1) ? (D1(Img.Lines, Img.Columns, up.line, up.column) + 1) : 1;
down.line = cur.line + 1;
down.column = cur.column;
down_id = D1(Img.Lines, Img.Columns, down.line, down.column) + 1;
right.line = cur.line;
right.column = cur.column + 1;
right_id = D1(Img.Lines, Img.Columns, right.line, right.column) + 1;
left.line = cur.line;
left.column = cur.column - 1;
left_id = (left.column >= 1) ? (D1(Img.Lines, Img.Columns, left.line, left.column) + 1) : 1;
//Add its neighbors in the Priority list
if((up.line>=Img.Macroblocks[i].LineStart && up.line<=Img.Macroblocks[i].LineEnd)
&& (up.column>=Img.Macroblocks[i].ColumnStart && up.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[up_id - 1] == -1 && ImgEdge.Buffer(up.line, up.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = up_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[up_id - 1] = 0;
}
}
if((down.line>=Img.Macroblocks[i].LineStart && down.line<=Img.Macroblocks[i].LineEnd)
&& (down.column>=Img.Macroblocks[i].ColumnStart && down.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[down_id - 1] == -1 && ImgEdge.Buffer(down.line, down.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = down_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[down_id - 1] = 0;
}
}
if((right.line>=Img.Macroblocks[i].LineStart && right.line<=Img.Macroblocks[i].LineEnd)
&& (right.column>=Img.Macroblocks[i].ColumnStart && right.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[right_id - 1] == -1 && ImgEdge.Buffer(right.line, right.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = right_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[right_id - 1] = 0;
}
}
if((left.line>=Img.Macroblocks[i].LineStart && left.line<=Img.Macroblocks[i].LineEnd)
&& (left.column>=Img.Macroblocks[i].ColumnStart && left.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[left_id - 1] == -1 && ImgEdge.Buffer(left.line, left.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = left_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[left_id - 1] = 0;
}
}
//Create a single pixel object
tmp.id = cur_id;
tmp.area = 1;
tmp.edge = TRUE;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
tmp.Sum.push_back(cur_val);
tmp.SumSq.push_back((cur_val*cur_val));
}
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
pass1.Objects.insert(make_pair(tmp.id, tmp));
pass1.raster[cur_id - 1] = cur_id;
tmp.clear();
edgecounter++;
}
}
}
//Edge additions END
//While the priority list is not empty
while (!mseg.PriorityList.empty()){
//Load the next priority object
tmp_priority_object = mseg.PriorityList.top();
pri = tmp_priority_object.primary;
sec = tmp_priority_object.secondary;
cur_id = tmp_priority_object.id;
mseg.PriorityList.pop();
//If pixel has been merged...goto end of while loop
if(pass1.raster[cur_id - 1] > 0) continue;
cur = D2(cur_id, Img.Columns);
best_h = Param.Scale; //The maximum heterogeneity allowed is the scale parameter
matches = 0;
//Load neigbors
up.line = cur.line - 1;
up.column = cur.column;
up_id = (up.line >= 1) ? (D1(Img.Lines, Img.Columns, up.line, up.column) + 1) : 1;
down.line = cur.line + 1;
down.column = cur.column;
down_id = D1(Img.Lines, Img.Columns, down.line, down.column) + 1;
right.line = cur.line;
right.column = cur.column + 1;
right_id = D1(Img.Lines, Img.Columns, right.line, right.column) + 1;
left.line = cur.line;
left.column = cur.column - 1;
left_id = (left.column >= 1) ? (D1(Img.Lines, Img.Columns, left.line, left.column) + 1) : 1;
//Check neighbors
//TODO: Put everything into arrays and loop 4 times...
if((up.line>=Img.Macroblocks[i].LineStart && up.line<=Img.Macroblocks[i].LineEnd)
&& (up.column>=Img.Macroblocks[i].ColumnStart && up.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[up_id - 1] <= 0){
//Calculate heterogeneity
up_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(up.line, up.column, b);
std = abs(cur_val - near_val)/2;
up_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (up_h < Param.Scale){
matches++;
if (up_h < best_h){
best_h = up_h;
best_id = up_id;//We will copy the best outside this loop in order to spare copies
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[up_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = up_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[up_id - 1] = 0;
}
}
}
if((down.line>=Img.Macroblocks[i].LineStart && down.line<=Img.Macroblocks[i].LineEnd)
&& (down.column>=Img.Macroblocks[i].ColumnStart && down.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[down_id - 1] <= 0){
//Calculate heterogeneity
down_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(down.line, down.column, b);
std = abs(cur_val - near_val)/2;
down_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (down_h < Param.Scale){
matches++;
if (down_h < best_h){
best_h = down_h;
best_id = down_id;//We will copy the best outside this loop in order to spare copies
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[down_id - 1] == -1){
tmp_priority_object.primary = ++pri;//+1;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = down_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[down_id - 1] = 0;
}
}
}
if((right.line>=Img.Macroblocks[i].LineStart && right.line<=Img.Macroblocks[i].LineEnd)
&& (right.column>=Img.Macroblocks[i].ColumnStart && right.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[right_id - 1] <= 0){
//Calculate heterogeneity
right_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(right.line, right.column, b);
std = abs(cur_val - near_val)/2;
right_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (right_h < Param.Scale){
matches++;
if (right_h < best_h){
best_h = right_h;
best_id = right_id;//We will copy the best outside this loop in order to spare copies
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[right_id - 1] == -1){
tmp_priority_object.primary = ++pri;//+1;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = right_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[right_id - 1] = 0;
}
}
}
if((left.line>=Img.Macroblocks[i].LineStart && left.line<=Img.Macroblocks[i].LineEnd)
&& (left.column>=Img.Macroblocks[i].ColumnStart && left.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[left_id - 1] <= 0){
//Calculate heterogeneity
left_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(left.line, left.column, b);
std = abs(cur_val - near_val)/2;
left_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (left_h < Param.Scale){
matches++;
if (left_h < best_h){
best_h = left_h;
best_id = left_id;//We will copy the best outside this loop in order to spare copies
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[left_id - 1] == -1){
tmp_priority_object.primary = pri+1;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = left_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[left_id - 1] = 0;
}
}
}
//Push it's neigbors into the priority list if they are not merged (done above)
//Check for match
if(matches){
//Check for the best match
best = D2(best_id, Img.Columns);
best_best_h = Param.Scale; //The maximum heterogeneity allowed is the scale parameter
//Load neigbors
best_up.line = best.line-1;
best_up.column = best.column;
best_up_id = (best_up.line >= 1) ? (D1(Img.Lines, Img.Columns, best_up.line, best_up.column) + 1) : 1;
best_down.line = best.line + 1;
best_down.column = best.column;
best_down_id = D1(Img.Lines, Img.Columns, best_down.line, best_down.column) + 1;
best_right.line = best.line;
best_right.column = best.column + 1;
best_right_id = D1(Img.Lines, Img.Columns, best_right.line, best_right.column) + 1;
best_left.line = best.line;
best_left.column = best.column -1;
best_left_id = (best_left.column >= 1) ? (D1(Img.Lines, Img.Columns, best_left.line, best_left.column) + 1) : 1;
//Check neighbors
if((best_up.line>=Img.Macroblocks[i].LineStart && best_up.line<=Img.Macroblocks[i].LineEnd)
&& (best_up.column>=Img.Macroblocks[i].ColumnStart && best_up.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_up_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_up_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_up_id - 1] = 0;
}
}
if((best_down.line>=Img.Macroblocks[i].LineStart && best_down.line<=Img.Macroblocks[i].LineEnd)
&& (best_down.column>=Img.Macroblocks[i].ColumnStart && best_down.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_down_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_down_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_down_id - 1] = 0;
}
}
if((best_right.line>=Img.Macroblocks[i].LineStart && best_right.line<=Img.Macroblocks[i].LineEnd)
&& (best_right.column>=Img.Macroblocks[i].ColumnStart && best_right.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_right_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_right_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_right_id - 1] = 0;
}
}
if((best_left.line>=Img.Macroblocks[i].LineStart && best_left.line<=Img.Macroblocks[i].LineEnd)
&& (best_left.column>=Img.Macroblocks[i].ColumnStart && best_left.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_left_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_left_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_left_id - 1] = 0;
}
}
//If yes create object, return value --> Update raster, clear temp object
mseg.last_id++;//add 1 to last id to use to the current object
tmp.id = mseg.last_id;
tmp.area = 2;
tmp.edge = FALSE;
mergecounter++;
//tmp.cycle = 1;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(best.line, best.column, b);
tmp.Sum.push_back((cur_val+near_val));
tmp.SumSq.push_back((cur_val*cur_val)+(near_val*near_val));
}
if(cur.line == best.line){//the object will have one BoundaryLine object
tmpBoundaryLine.Line = cur.line;
if(cur.column<best.column){
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = best.column;
}
else{
tmpBoundaryLine.ColumnStart = best.column;
tmpBoundaryLine.ColumnEnd = cur.column;
}
tmp.Boundary.push_back(tmpBoundaryLine);
}
else if(cur.line < best.line){//the object will have two BoundaryLine objects
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
tmpBoundaryLine.Line = best.line;
tmpBoundaryLine.ColumnStart = best.column;
tmpBoundaryLine.ColumnEnd = best.column;
tmp.Boundary.push_back(tmpBoundaryLine);
}
else {
tmpBoundaryLine.Line = best.line;
tmpBoundaryLine.ColumnStart = best.column;
tmpBoundaryLine.ColumnEnd = best.column;
tmp.Boundary.push_back(tmpBoundaryLine);
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
}
pass1.Objects.insert(make_pair(tmp.id, tmp));//insert will work better here...
pass1.raster[cur_id - 1] = tmp.id;
pass1.raster[best_id - 1] = tmp.id;
tmp.clear();
}
else{//if cur has no matches
//create single pixel object --> Update raster, clear temp object
tmp.id = cur_id;
tmp.area = 1;
tmp.edge = FALSE;
//tmp.cycle = 1;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
tmp.Sum.push_back(cur_val);
tmp.SumSq.push_back((cur_val*cur_val));
}
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
pass1.Objects.insert(make_pair(tmp.id, tmp));//insert here to
pass1.raster[cur_id - 1] = cur_id;
tmp.clear();
}
}
//TODO:Check if some pixels have not been treated and create single pixel objects --> Update raster
}
//Create topology --> Load Topology
cout << endl << "Calculating overall topology now..." << endl;
Neighbor n;
n.merging_heterogeneity = 0.0;
for(int row=1; row<=Img.Lines; row++){
for(int col=1; col<=Img.Columns; col++){
cur.line = row;
cur.column = col;
up.line = cur.line-1;
up.column = cur.column;
down.line = cur.line + 1;
down.column = down.column;
right.line = cur.line;
right.column = cur.column + 1;
left.line = cur.line;
left.column = cur.column -1;
cur_id = pass1.raster[D1(Img.Lines, Img.Columns, cur.line, cur.column)];
if ((up.line>0 && up.line<=Img.Lines) && (up.column>0 && up.column<=Img.Columns)){
up_id = pass1.raster[D1(Img.Lines, Img.Columns, up.line, up.column)];
if(cur_id != up_id){
n.id = up_id;
if(pass1.Objects[cur_id].check_neighbor(up_id) == FALSE){
pass1.Objects[cur_id].Neighbors.push_back(n);
}
}
}
if ((down.line>0 && down.line<=Img.Lines) && (down.column>0 && down.column<=Img.Columns)){
down_id = pass1.raster[D1(Img.Lines, Img.Columns, down.line, down.column)];
if(cur_id != down_id){
n.id = down_id;
if(pass1.Objects[cur_id].check_neighbor(down_id) == FALSE){//Maybe disable and use fix() for speed...???
pass1.Objects[cur_id].Neighbors.push_back(n);
}
}
}
if ((right.line>0 && right.line<=Img.Lines) && (right.column>0 && right.column<=Img.Columns)){
right_id = pass1.raster[D1(Img.Lines, Img.Columns, right.line, right.column)];
if(cur_id != right_id){
n.id = right_id;
if(pass1.Objects[cur_id].check_neighbor(right_id) == FALSE){
pass1.Objects[cur_id].Neighbors.push_back(n);
}
}
}
if ((left.line>0 && left.line<=Img.Lines) && (left.column>0 && left.column<=Img.Columns)){
left_id = pass1.raster[D1(Img.Lines, Img.Columns, left.line, left.column)];
if(cur_id != left_id){
n.id = left_id;
if(pass1.Objects[cur_id].check_neighbor(left_id) == FALSE){
pass1.Objects[cur_id].Neighbors.push_back(n);
}
}
}
}
}
cout << "First pass completed succesfully!" << endl;
cout << "Objects allocated in first pass Level: " << pass1.Objects.size() << endl;
cout << "Edge Objects in this pass: " << edgecounter << endl;
return mergecounter;
}
int FastEdge_Mode::firstpass(Level& pass1, ERS_Image& Img, ERS_Image& ImgEdge, MSEG_Init& mseg, float level_ID, MSEG_Param& Param, Level& super_level){
int mergecounter = 0;
int edgecounter = 0;
pass1.raster.reserve(Img.Lines*Img.Columns);
pass1.cycles = 1;
pass1.Lines = Img.Lines;
pass1.Columns = Img.Columns;
mseg.last_id = (Img.Lines*Img.Columns); //Set the first object id
//Let all the raster become -1
for (int i=0; i<(Img.Lines*Img.Columns); i++){
pass1.raster.push_back(-1);
//pass1.raster[i] = -1;//Solution 2, without reallocating memory into the vector
}
//Copy the id number
pass1.HierarchyID = level_ID;
//Copy segmentation parameters into new level
pass1.ScaleParameter = Param.Scale;
pass1.Color = Param.Color;
pass1.Compactness = Param.Compact;
pass1.Edge = Param.Edge;
//Declare a temporary object
Object tmp;
//Generic Declarations
BoundaryLine tmpBoundaryLine;
PriorityObject tmp_priority_object;
pixel cur, up, down, right, left, best, best_up, best_down, best_right, best_left, best_best;
int cur_id, up_id, down_id, right_id, left_id, best_id, best_best_id;
int best_up_id, best_down_id, best_right_id, best_left_id;
int i, c, l, pri, sec, matches, pri_edge;
float best_h, up_h, down_h, left_h, right_h, best_up_h, best_down_h, best_right_h, best_left_h, best_best_h;
float std;
float cur_val, near_val;
//Check the SPE result number
if (mseg.StartingPoints.size() != Img.Macroblocks.size()){
cout << "Error in SPE result" << endl << "Quiting at first pass..." << endl;
exit(1);
}
int msize = Img.Macroblocks.size();
//For every macroblock
for(i=0;i<(Img.MacroLines * Img.MacroColumns);i++){
//Assume each pixel is an object and assign them false ids in order to use the priority_queue
//The pixel false id is the 1D [] representation inside the raster vector
pri = 1;//During first pass only primary is usefull.(inside macroblock)
sec = 1;
pri_edge = 1000000;
//Load the Starting Point
cur.line = mseg.StartingPoints[i].line;
cur.column = mseg.StartingPoints[i].column;
cur_id = D1(Img.Lines, Img.Columns, cur.line, cur.column) + 1;
//Check the boundary for the starting point
if ((cur.line<Img.Macroblocks[i].LineStart || cur.line>Img.Macroblocks[i].LineEnd)
||(cur.column<Img.Macroblocks[i].ColumnStart || cur.column>Img.Macroblocks[i].ColumnEnd)){
cout << "Starting point" << i << "out of bounds" << endl
<< "Quiting at first pass..." << endl;
exit(1);
}
//Push the first pixel to the priority_queue
tmp_priority_object.primary = pri;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = cur_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[cur_id - 1] = 0; //Flag that it is loaded into priority list
//Edge additions START
for(l=Img.Macroblocks[i].LineStart;l<=Img.Macroblocks[i].LineEnd;l++){
for(c=Img.Macroblocks[i].ColumnStart;c<=Img.Macroblocks[i].ColumnEnd;c++){
if(ImgEdge.Buffer(l, c, 1) == 255.0){
cur.line = l;
cur.column = c;
cur_id = D1(Img.Lines, Img.Columns, cur.line, cur.column) + 1;
//Load neigbors
up.line = cur.line - 1;
up.column = cur.column;
up_id = (up.line >= 1) ? (D1(Img.Lines, Img.Columns, up.line, up.column) + 1) : 1;
down.line = cur.line + 1;
down.column = cur.column;
down_id = D1(Img.Lines, Img.Columns, down.line, down.column) + 1;
right.line = cur.line;
right.column = cur.column + 1;
right_id = D1(Img.Lines, Img.Columns, right.line, right.column) + 1;
left.line = cur.line;
left.column = cur.column - 1;
left_id = (left.column >= 1) ? (D1(Img.Lines, Img.Columns, left.line, left.column) + 1) : 1;
//Add its neighbors in the Priority list
if((up.line>=Img.Macroblocks[i].LineStart && up.line<=Img.Macroblocks[i].LineEnd)
&& (up.column>=Img.Macroblocks[i].ColumnStart && up.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[up_id - 1] == -1 && ImgEdge.Buffer(up.line, up.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = up_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[up_id - 1] = 0;
}
}
if((down.line>=Img.Macroblocks[i].LineStart && down.line<=Img.Macroblocks[i].LineEnd)
&& (down.column>=Img.Macroblocks[i].ColumnStart && down.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[down_id - 1] == -1 && ImgEdge.Buffer(down.line, down.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = down_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[down_id - 1] = 0;
}
}
if((right.line>=Img.Macroblocks[i].LineStart && right.line<=Img.Macroblocks[i].LineEnd)
&& (right.column>=Img.Macroblocks[i].ColumnStart && right.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[right_id - 1] == -1 && ImgEdge.Buffer(right.line, right.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = right_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[right_id - 1] = 0;
}
}
if((left.line>=Img.Macroblocks[i].LineStart && left.line<=Img.Macroblocks[i].LineEnd)
&& (left.column>=Img.Macroblocks[i].ColumnStart && left.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[left_id - 1] == -1 && ImgEdge.Buffer(left.line, left.column, 1) != 255.0){
tmp_priority_object.primary = ++pri_edge;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = left_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[left_id - 1] = 0;
}
}
//Create a single pixel object
tmp.id = cur_id;
tmp.area = 1;
tmp.edge = TRUE;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
tmp.Sum.push_back(cur_val);
tmp.SumSq.push_back((cur_val*cur_val));
}
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
pass1.Objects.insert(make_pair(tmp.id, tmp));
pass1.raster[cur_id - 1] = cur_id;
tmp.clear();
edgecounter++;
}
}
}
//Edge additions END
//While the priority list is not empty
while (!mseg.PriorityList.empty()){
//Load the next priority object
tmp_priority_object = mseg.PriorityList.top();
pri = tmp_priority_object.primary;
sec = tmp_priority_object.secondary;
cur_id = tmp_priority_object.id;
mseg.PriorityList.pop();//Perhaps to the end????
//If pixel has been merged...goto end of while loop
if(pass1.raster[cur_id - 1] > 0) continue;
cur = D2(cur_id, Img.Columns);
best_h = Param.Scale; //The maximum heterogeneity allowed is the scale parameter
matches = 0;
//Load neigbors
up.line = cur.line - 1;
up.column = cur.column;
up_id = (up.line >= 1) ? (D1(Img.Lines, Img.Columns, up.line, up.column) + 1) : 1;
down.line = cur.line + 1;
down.column = cur.column;
down_id = D1(Img.Lines, Img.Columns, down.line, down.column) + 1;
right.line = cur.line;
right.column = cur.column + 1;
right_id = D1(Img.Lines, Img.Columns, right.line, right.column) + 1;
left.line = cur.line;
left.column = cur.column - 1;
left_id = (left.column >= 1) ? (D1(Img.Lines, Img.Columns, left.line, left.column) + 1) : 1;
//Check neighbors
//TODO: Put everything into arrays and loop 4 times...
if((up.line>=Img.Macroblocks[i].LineStart && up.line<=Img.Macroblocks[i].LineEnd)
&& (up.column>=Img.Macroblocks[i].ColumnStart && up.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[up_id - 1] <= 0){
if(super_level.raster[up_id-1]==super_level.raster[cur_id-1]){
//Calculate heterogeneity
up_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(up.line, up.column, b);
std = abs(cur_val - near_val)/2;
up_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (up_h < Param.Scale){
matches++;
if (up_h < best_h){
best_h = up_h;
best_id = up_id;//We will copy the best outside this loop in order to spare copies
}
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[up_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = up_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[up_id - 1] = 0;
}
}
}
if((down.line>=Img.Macroblocks[i].LineStart && down.line<=Img.Macroblocks[i].LineEnd)
&& (down.column>=Img.Macroblocks[i].ColumnStart && down.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[down_id - 1] <= 0){
if(super_level.raster[down_id-1]==super_level.raster[cur_id-1]){
//Calculate heterogeneity
down_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(down.line, down.column, b);
std = abs(cur_val - near_val)/2;
down_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (down_h < Param.Scale){
matches++;
if (down_h < best_h){
best_h = down_h;
best_id = down_id;//We will copy the best outside this loop in order to spare copies
}
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[down_id - 1] == -1){
tmp_priority_object.primary = ++pri;//+1;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = down_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[down_id - 1] = 0;
}
}
}
if((right.line>=Img.Macroblocks[i].LineStart && right.line<=Img.Macroblocks[i].LineEnd)
&& (right.column>=Img.Macroblocks[i].ColumnStart && right.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[right_id - 1] <= 0){
if(super_level.raster[right_id-1]==super_level.raster[cur_id-1]){
//Calculate heterogeneity
right_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(right.line, right.column, b);
std = abs(cur_val - near_val)/2;
right_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (right_h < Param.Scale){
matches++;
if (right_h < best_h){
best_h = right_h;
best_id = right_id;//We will copy the best outside this loop in order to spare copies
}
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[right_id - 1] == -1){
tmp_priority_object.primary = ++pri;//+1;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = right_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[right_id - 1] = 0;
}
}
}
if((left.line>=Img.Macroblocks[i].LineStart && left.line<=Img.Macroblocks[i].LineEnd)
&& (left.column>=Img.Macroblocks[i].ColumnStart && left.column<=Img.Macroblocks[i].ColumnEnd)){
if(pass1.raster[left_id - 1] <= 0){
if(super_level.raster[left_id-1]==super_level.raster[cur_id-1]){
//Calculate heterogeneity
left_h = 0.0;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(left.line, left.column, b);
std = abs(cur_val - near_val)/2;
left_h += Img.BandWeight[b]* 2 * std;
}
//Is it a match? --> matches++ --> compare to best_h
if (left_h < Param.Scale){
matches++;
if (left_h < best_h){
best_h = left_h;
best_id = left_id;//We will copy the best outside this loop in order to spare copies
}
}
}
//if raster value <0 --> push pixel in queue
if (pass1.raster[left_id - 1] == -1){
tmp_priority_object.primary = pri+1;
tmp_priority_object.secondary = sec;
tmp_priority_object.id = left_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[left_id - 1] = 0;
}
}
}
//Push it's neigbors into the priority list if they are not merged (done above)
//Check for match
if(matches){
//Check for the best match
best = D2(best_id, Img.Columns);
best_best_h = Param.Scale; //The maximum heterogeneity allowed is the scale parameter
//Load neigbors
best_up.line = best.line-1;
best_up.column = best.column;
best_up_id = (best_up.line >= 1) ? (D1(Img.Lines, Img.Columns, best_up.line, best_up.column) + 1) : 1;
best_down.line = best.line + 1;
best_down.column = best.column;
best_down_id = D1(Img.Lines, Img.Columns, best_down.line, best_down.column) + 1;
best_right.line = best.line;
best_right.column = best.column + 1;
best_right_id = D1(Img.Lines, Img.Columns, best_right.line, best_right.column) + 1;
best_left.line = best.line;
best_left.column = best.column -1;
best_left_id = (best_left.column >= 1) ? (D1(Img.Lines, Img.Columns, best_left.line, best_left.column) + 1) : 1;
//Check neighbors
if((best_up.line>=Img.Macroblocks[i].LineStart && best_up.line<=Img.Macroblocks[i].LineEnd)
&& (best_up.column>=Img.Macroblocks[i].ColumnStart && best_up.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_up_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_up_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_up_id - 1] = 0;
}
}
if((best_down.line>=Img.Macroblocks[i].LineStart && best_down.line<=Img.Macroblocks[i].LineEnd)
&& (best_down.column>=Img.Macroblocks[i].ColumnStart && best_down.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_down_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_down_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_down_id - 1] = 0;
}
}
if((best_right.line>=Img.Macroblocks[i].LineStart && best_right.line<=Img.Macroblocks[i].LineEnd)
&& (best_right.column>=Img.Macroblocks[i].ColumnStart && best_right.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_right_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_right_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_right_id - 1] = 0;
}
}
if((best_left.line>=Img.Macroblocks[i].LineStart && best_left.line<=Img.Macroblocks[i].LineEnd)
&& (best_left.column>=Img.Macroblocks[i].ColumnStart && best_left.column<=Img.Macroblocks[i].ColumnEnd)){
if (pass1.raster[best_left_id - 1] == -1){
tmp_priority_object.primary = ++pri;//pri + 1
tmp_priority_object.secondary = sec;
tmp_priority_object.id = best_left_id;
mseg.PriorityList.push(tmp_priority_object);
pass1.raster[best_left_id - 1] = 0;
}
}
//If yes create object, return value --> Update raster, clear temp object
mseg.last_id++;//add 1 to last id to use to the current object
tmp.id = mseg.last_id;
tmp.area = 2;
tmp.edge = FALSE;
mergecounter++;
//tmp.cycle = 1;
for (int b=1; b<=Img.Bands; b++){
cur_val = Img.Buffer(cur.line, cur.column, b);
near_val = Img.Buffer(best.line, best.column, b);
tmp.Sum.push_back((cur_val+near_val));
tmp.SumSq.push_back((cur_val*cur_val)+(near_val*near_val));
}
if(cur.line == best.line){//the object will have one BoundaryLine object
tmpBoundaryLine.Line = cur.line;
if(cur.column<best.column){
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = best.column;
}
else{
tmpBoundaryLine.ColumnStart = best.column;
tmpBoundaryLine.ColumnEnd = cur.column;
}
tmp.Boundary.push_back(tmpBoundaryLine);
}
else if(cur.line < best.line){//the object will have two BoundaryLine objects
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
tmpBoundaryLine.Line = best.line;
tmpBoundaryLine.ColumnStart = best.column;
tmpBoundaryLine.ColumnEnd = best.column;
tmp.Boundary.push_back(tmpBoundaryLine);
}
else {
tmpBoundaryLine.Line = best.line;
tmpBoundaryLine.ColumnStart = best.column;
tmpBoundaryLine.ColumnEnd = best.column;
tmp.Boundary.push_back(tmpBoundaryLine);
tmpBoundaryLine.Line = cur.line;
tmpBoundaryLine.ColumnStart = cur.column;
tmpBoundaryLine.ColumnEnd = cur.column;
tmp.Boundary.push_back(tmpBoundaryLine);
}
pass1.Objects.insert(make_pair(tmp.id, tmp));//insert will work better here...
pass1.raster[cur_id - 1] = tmp.id;
pass1.raster[best_id - 1] = tmp.id;
tmp.clear();
}