Array * LocalMedianFilter(RasterizedImage & img, ParaSet & imgPara, Array * original, int filterRadius, double threshold ){
uint32 *orig = AUINT32(original);
Array *median = Make_Array_With_Shape(PLAIN_KIND, UINT32_TYPE, Coord2(original->dims[1], original->dims[0]));
uint32 *med = AUINT32(median);
Use_Extend_Boundary();
Frame * f = Make_Frame(original,Coord2(2*filterRadius+1,2*filterRadius+1),Coord2(filterRadius, filterRadius));
Histogram * h = Make_Histogram(UVAL,img.GetDepth(),ValU(1),ValU(0));
Place_Frame(f,0);
for (Indx_Type p = 0; p < median->size; p++){
Empty_Histogram(h);
Histagain_Array(h,f,0);
h->counts[orig[p]]--; // excludes the height of p in the calculation of the median
if (abs(static_cast<int>(orig[p]) - Percentile2Bin(h,.5)) > threshold) { // replaces a pixel only if the different between the pixel value and the median is greater than the threshold
med[p] = Percentile2Bin(h,.5);
} else {
med[p] = orig[p];
}
Move_Frame_Forward(f);
}
Kill_Histogram(h);
Kill_Frame(f);
if (imgPara.verbose){
std::cout << "Planes filtered" << std::endl;
}
return median;
}
/*
Median filter that only modifies a pixel when it significantly differs from the median of its 8-connected neighborhood that is weighted by the variance
@param img: input image
@param imgPara: struct with parameters
@param original: current height map
@param filterRadius: radius to define the 8-connected neighborhood
@param threshold: threshold to identify pixels that need to be modified
*/
Array * LocalMedianFilter_InclVar(RasterizedImage & img, ParaSet & imgPara, Array * original, int filterRadius, double threshold){
uint32 *orig = AUINT32(original);
Array *median = Make_Array_With_Shape(PLAIN_KIND, UINT32_TYPE, Coord2(original->dims[1], original->dims[0]));
uint32 *med = AUINT32(median);
Use_Extend_Boundary();
Frame * f = Make_Frame(original,Coord2(2*filterRadius+1,2*filterRadius+1),Coord2(filterRadius, filterRadius));
// Frame to compute the variance in intensity of the current grid element
Frame * varF = Make_Frame(img.GetImage(),Coord3(1, imgPara.radius,imgPara.radius),Coord3(0, 0, 0));
Histogram * varH = Make_Histogram(UVAL,256,ValU(1),ValU(0));
uint32 * data;
Place_Frame(f,0);
Place_Frame(varF, 0);
for (Dimn_Type y = 0; y <= img.GetHeight()-imgPara.radius; y += imgPara.radius){
for (Dimn_Type x = 0; x <= img.GetWidth()-imgPara.radius; x += imgPara.radius){
Indx_Type pHM = (y/imgPara.radius) * original->dims[0] + (x/imgPara.radius);
Place_Frame(f, pHM);
data = (uint32 *) Frame_Values(f);
std::vector<double> depths;
double sum = 0;
double n = 0;
for (int i = 0; i < AForm_Size(f); i++) {
Indx_Type p = Coord2IdxA(img.GetImage(), Coord3(data[i],y, x));
Place_Frame(varF, p);
Histagain_Array(varH,varF,0);
sum += Histogram_Variance(varH) * data[i];
n += Histogram_Variance(varH);
for (int j=0; j< floor(Histogram_Variance(varH)/10); j++) { // weight the current height with the variance
depths.push_back(data[i]);
}
}
double weightedMedian = VectorMedian(depths);
if (abs(orig[pHM] - weightedMedian) > threshold ) {
med[pHM] = floor(weightedMedian);
} else {
med[pHM] = orig[pHM];
}
}
}
Kill_Histogram(varH);
Kill_Frame(varF);
Kill_Frame(f);
return median;
}
double ComputeSmoothness(Array * heightMap) {
Array * distances = Make_Array_With_Shape(PLAIN_KIND,UINT32_TYPE,Coord2(heightMap->dims[1], heightMap->dims[0]));
uint32 * distVals = AUINT32(distances);
uint32 * hmVals = AUINT32(heightMap);
Use_Reflective_Boundary();
HeightMapRange range = GetLevelRange(heightMap);
// frame defines the local neighborhood
Frame * f = Make_Frame(heightMap,Coord2(3,3),Coord2(1,1));
Histogram * h = Make_Histogram(UVAL,range.maxLayer,ValU(1),ValU(0));
Place_Frame(f,0);
for (Indx_Type i=0; i< heightMap->size; i++) {
Empty_Histogram(h);
Histagain_Array(h, f, 0);
int middleBin = Value2Bin(h, ValU(hmVals[i])); // To determine the median value of the pixel's neighborhood, we exlude the current pixel i from the histogram
h->counts[middleBin]--;
distVals[i] = std::abs(static_cast<double>(hmVals[i]) - static_cast<double>(Percentile2Bin(h, 0.5)));
}
#ifdef DEVELOP
Write_Image("HeightMapSmoothness", distances, DONT_PRESS);
#endif
Empty_Histogram(h);
Histagain_Array(h, distances, 0);
double meanDistance = Histogram_Mean(h);
std::cout << "Smoothness:\n Mean distance: " << meanDistance << "\n Sd: " << Histogram_Sigma(h) << std::endl;
Free_Histogram(h);
Free_Frame(f);
Free_Array(distances);
return meanDistance;
}
Array * MedianFilter(RasterizedImage & img, ParaSet & imgPara, Array *original, int filterRadius){
// output image
Array *median = Make_Array_With_Shape(PLAIN_KIND,UINT32_TYPE,Coord2(original->dims[1], original->dims[0]));
uint32 *med = AUINT32(median);
uint32 *orig = AUINT32(original);
#ifdef DEVELOP
Array *variance = Make_Array_With_Shape(PLAIN_KIND,UINT32_TYPE,Coord2(original->dims[1], original->dims[0]));
uint32 *var = AUINT32(variance);
#endif
Use_Reflective_Boundary();
// frames defines the local neighborhood
Frame * f = Make_Frame(original,Coord2(2*filterRadius+1,2*filterRadius+1),Coord2(filterRadius,filterRadius));
Histogram * h = Make_Histogram(UVAL,img.GetDepth(),ValU(1),ValU(0));
Place_Frame(f,0);
for (Indx_Type p = 0; p < median->size; p++){
Empty_Histogram(h);
Histagain_Array(h,f,0);
h->counts[orig[p]]--; // excludes the height of p in the calculation of the median
med[p] = Percentile2Bin(h,.5); // median is given at 50th percentile
#ifdef DEVELOP
var[p] = 10*Histogram_Sigma(h);
#endif
Move_Frame_Forward(f);
}
Kill_Histogram(h);
Kill_Frame(f);
#ifdef DEVELOP
ShowArray(img, imgPara, "median.tif", median);
ShowArray(img, imgPara, "variance.tif", variance);
Free_Array(variance);
#endif
if (imgPara.verbose){
std::cout << "Planes filtered" << std::endl;
}
return (median);
}
int main(int argc, char *argv[])
{ FILE *output;
Process_Arguments(argc,argv,Spec,0);
#ifdef PROGRESS
printf("\nParameters: c=%g e=%g s=%d\n",
Get_Double_Arg("-c"),Get_Double_Arg("-e"),Get_Int_Arg("-s"));
printf("SubFolder: %s\n",Get_String_Arg("folder"));
printf("CoreName: %s\n",Get_String_Arg("core"));
fflush(stdout);
#endif
RezFolder = strdup(Get_String_Arg("folder"));
if (RezFolder[strlen(RezFolder)-1] == '/')
RezFolder[strlen(RezFolder)-1] = '\0';
if (mkdir(RezFolder,S_IRWXU|S_IRWXG|S_IRWXO))
{ if (errno != EEXIST)
{ fprintf(stderr,"Error trying to create directory %s: %s\n",RezFolder,strerror(errno));
exit (1);
}
}
CoreName = strdup(Get_String_Arg("core"));
sprintf(NameBuf,"%s.neu",CoreName);
output = fopen(NameBuf,"w");
fprintf(output,"NEUSEP: Version 0.9\n");
{ Histogram *hist;
int curchan;
int maxchans;
int i, n;
n = Get_Repeat_Count("inputs");
fwrite(&n,sizeof(int),1,output);
hist = Make_Histogram(UVAL,0x10000,VALU(1),VALU(0));
maxchans = 0;
for (i = 0; i < n; i++)
{
curchan = NumChans;
maxchans = Read_All_Channels(Get_String_Arg("inputs",i),maxchans);
int channelsInCurrentFile=NumChans-curchan;
{ Size_Type sum, max;
Indx_Type p;
int j, wch;
uint16 *val;
max = -1;
for (j = curchan; j < NumChans; j++)
{ val = AUINT16(Images[j]);
sum = 0;
for (p = 0; p < Images[j]->size; p++)
sum += val[p];
if (sum > max)
{ max = sum;
wch = j;
}
}
fprintf(output,"%s\n",Get_String_Arg("inputs",i));
j = wch-curchan;
fwrite(&j,sizeof(int),1,output);
#ifdef PROGRESS
printf("\n Eliminating channel %d from %s\n",j+1,Get_String_Arg("inputs",i));
fflush(stdout);
#endif
{
// Section to write out the reference channel
printf("\n Considering reference channel output, channelsInCurrentFile=%d\n", channelsInCurrentFile);
fflush(stdout);
if (channelsInCurrentFile>2) { // should work with both lsm pair with channels=3, or raw file with channels=4
sprintf(NameBuf,"%s/Reference.tif",RezFolder,CoreName,i);
Write_Image(NameBuf,Images[wch],LZW_PRESS);
}
}
Free_Array(Images[wch]);
NumChans -= 1;
for (j = wch; j < NumChans; j++)
Images[j] = Images[j+1];
}
{ int j, ceil;
Indx_Type p;
uint16 *val;
for (j = curchan; j < NumChans; j++)
{
Histagain_Array(hist,Images[j],0);
ceil = Percentile2Bin(hist,1e-5);
if (ceil==0) {
fprintf(stderr, "Channel must have non-zero values for this program to function\n");
exit(1);
}
#ifdef PROGRESS
printf(" Clipping channel %d at ceil = %d\n",j,ceil); fflush(stdout);
fflush(stdout);
#endif
val = AUINT16(Images[j]);
for (p = 0; p < Images[j]->size; p++)
{
if (val[p] > ceil)
val[p] = ceil;
val[p] = (val[p]*4095)/ceil;
}
// Convert_Array_Inplace(Images[j],PLAIN_KIND,UINT8_TYPE,8,0);
}
}
}
Free_Histogram(hist);
printf("Starting ConsolidatedSignal.tif section\n");
fflush(stdout);
// NA addition: write tif with re-scaled intensities to serve as basis for mask file
{
Array *signalStack;
signalStack = Make_Array(RGB_KIND,UINT8_TYPE,3,Images[0]->dims);
uint8 *sp=AUINT8(signalStack);
int m;
Indx_Type signalIndex;
signalIndex=0;
for (m=0;m<NumChans;m++) {
sprintf(NameBuf, "%s/Signal_%d.tif", RezFolder, m);
printf("Writing 16-bit channel file %s...", NameBuf);
Write_Image(NameBuf, Images[m], LZW_PRESS);
printf("done\n");
uint16 *ip=AUINT16(Images[m]);
Indx_Type channelIndex;
for (channelIndex=0;channelIndex<Images[m]->size;channelIndex++) {
int value=ip[channelIndex]/16;
if (value>255) {
value=255;
}
sp[signalIndex++]=value; // convert 12-bit to 8-bit
}
}
sprintf(NameBuf,"%s/ConsolidatedSignal.tif", RezFolder);
printf("Writing 8-bit consolidated signal file %s...", NameBuf);
Write_Image(NameBuf,signalStack,LZW_PRESS);
printf("done");
//Free_Array(signalStack); - this is causing a bug
}
printf("Finished ConsolidatedSignal.tif section\n");
fflush(stdout);
}
{ int i;
Segmentation *segs;
Overlaps *ovl;
Clusters *clust;
int numneur;
Region **neurons;
segs = (Segmentation *) Guarded_Malloc(sizeof(Segmentation)*NumChans,Program_Name());
for (i = 0; i < NumChans; i++)
{ Segment_Channel(Images[i],segs+i);
if (i == 0)
segs[i].base = 0;
else
segs[i].base = segs[i-1].base + segs[i-1].nsegs;
printf("channel=%d segmentBase=%d\n", i, segs[i].base);
}
ovl = Find_Overlaps(segs);
clust = Merge_Segments(segs,ovl);
neurons = Segment_Clusters(segs,ovl,clust,&numneur);
if (Is_Arg_Matched("-gp"))
Output_Clusters(segs,ovl,clust);
if (Is_Arg_Matched("-nr"))
Output_Neurons(numneur,neurons,1);
// Added for NA
Output_Consolidated_Mask(numneur,neurons,1);
fwrite(&numneur,sizeof(int),1,output);
for (i = 0; i < numneur; i++)
Write_Region(neurons[i],output);
#ifdef PROGRESS
printf("\nProduced %d neurons/fragments in %s.neu\n",numneur,CoreName);
fflush(stdout);
#endif
printf("DEBUG: starting cleanup\n");
fflush(stdout);
for (i = 0; i < numneur; i++) {
printf("DEBUG: calling Kill_Region on neuron=%d\n", i);
fflush(stdout);
Kill_Region(neurons[i]);
}
printf("DEBUG: calling Kill_Clusters\n");
fflush(stdout);
Kill_Clusters(clust);
printf("DEBUG: calling Kill_Overlaps\n");
fflush(stdout);
//Kill_Overlaps(ovl); - causing a bug
printf("DEBUG: starting Kill_Segmentation loop\n");
fflush(stdout);
for (i = 0; i < NumChans; i++) {
printf("DEBUG: Kill_Segmentation on index=%d\n", i);
fflush(stdout);
Kill_Segmentation(segs+i);
}
printf("DEBUG: calling free() on segs\n");
fflush(stdout);
free(segs);
}
printf("DEBUG: starting filestream cleanup\n");
fflush(stdout);
{ int i;
fclose(output);
free(CoreName);
free(RezFolder);
for (i = 0; i < NumChans; i++)
Kill_Array(Images[i]);
free(Images);
}
#ifdef VERBOSE
printf("\nDid I free all arrays?:\n");
Print_Inuse_List(stdout,4);
#endif
exit (0);
}