Prune branches from the skeleton. More...

#include <processor.h>

Inheritance diagram for EMAN::PruneSkeletonProcessor:

Collaboration diagram for EMAN::PruneSkeletonProcessor:

[legend]

Public Member Functions
virtual void	process_inplace (EMData *image)
	To process an image in-place. More...

virtual EMData *	process (const EMData *const image)
	To proccess an image out-of-place. More...

virtual string	get_name () const
	Get the processor's name. More...

string	get_desc () const
	Get the descrition of this specific processor. More...

virtual TypeDict	get_param_types () const
	Get processor parameter information in a dictionary. More...

Public Member Functions inherited from EMAN::Processor
virtual	~Processor ()

virtual void	process_list_inplace (vector< EMData * > &images)
	To process multiple images using the same algorithm. More...

virtual Dict	get_params () const
	Get the processor parameters in a key/value dictionary. More...

virtual void	set_params (const Dict &new_params)
	Set the processor parameters using a key/value dictionary. More...

Static Public Member Functions
static Processor *	NEW ()

Static Public Member Functions inherited from EMAN::Processor
static string	get_group_desc ()
	Get the description of this group of processors. More...

static void	EMFourierFilterInPlace (EMData *fimage, Dict params)
	Compute a Fourier-filter processed image in place. More...

static EMData *	EMFourierFilter (EMData *fimage, Dict params)
	Compute a Fourier-processor processed image without altering the original image. More...

Static Public Attributes
static const string	NAME = "morph.prune"

Additional Inherited Members
Public Types inherited from EMAN::Processor
enum	fourier_filter_types { TOP_HAT_LOW_PASS , TOP_HAT_HIGH_PASS , TOP_HAT_BAND_PASS , TOP_HOMOMORPHIC , GAUSS_LOW_PASS , GAUSS_HIGH_PASS , GAUSS_BAND_PASS , GAUSS_INVERSE , GAUSS_HOMOMORPHIC , BUTTERWORTH_LOW_PASS , BUTTERWORTH_HIGH_PASS , BUTTERWORTH_HOMOMORPHIC , KAISER_I0 , KAISER_SINH , KAISER_I0_INVERSE , KAISER_SINH_INVERSE , SHIFT , TANH_LOW_PASS , TANH_HIGH_PASS , TANH_HOMOMORPHIC , TANH_BAND_PASS , RADIAL_TABLE , CTF_ }
	Fourier filter Processor type enum. More...

Protected Attributes inherited from EMAN::Processor
Dict	params

Detailed Description

Prune branches from the skeleton.

Remove a piece when the minimum distance through density from an endpoint to the nearest branch point is shorter than a given value.

Author: : Muyuan Chen

Date: : 04/2015

Definition at line 9623 of file processor.h.

Member Function Documentation

◆ get_desc()

string EMAN::PruneSkeletonProcessor::get_desc ( ) const

inlinevirtual

Get the descrition of this specific processor.

This function must be overwritten by a subclass.

Returns: The description of this processor.

Implements EMAN::Processor.

Definition at line 9637 of file processor.h.

                {
                        return "Prune branches from the skeleton. Remove a piece when the minimum distance through density from an endpoint to the nearest branch point is shorter than a given value.";
                }

◆ get_name()

virtual string EMAN::PruneSkeletonProcessor::get_name ( ) const

inlinevirtual

Get the processor's name.

Each processor is identified by a unique name.

Returns: The processor's name.

Implements EMAN::Processor.

Definition at line 9629 of file processor.h.

                {
                        return NAME;
                }

References NAME.

◆ get_param_types()

virtual TypeDict EMAN::PruneSkeletonProcessor::get_param_types ( ) const

inlinevirtual

Get processor parameter information in a dictionary.

Each parameter has one record in the dictionary. Each record contains its name, data-type, and description.

Returns: A dictionary containing the parameter info.

Reimplemented from EMAN::Processor.

Definition at line 9641 of file processor.h.

                {
                        TypeDict d;
                        d.put("thresh", EMObject::FLOAT, "The threshold to binarize the map.");
                        d.put("verbose", EMObject::INT, "Verbose");
                        d.put("returnlength", EMObject::BOOL, "Return the distance of each white pixel to its nearest branch. Does not do the prunning.");
                        d.put("maxdist", EMObject::INT, "Maximum distance from the endpoint to branchpoint");
                        return d;
                }

References EMAN::EMObject::BOOL, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().

◆ NEW()

static Processor * EMAN::PruneSkeletonProcessor::NEW ( )

inlinestatic

Definition at line 9633 of file processor.h.

                {
                        return new PruneSkeletonProcessor();
                }

◆ process()

EMData * PruneSkeletonProcessor::process ( const EMData *const image )

virtual

To proccess an image out-of-place.

For those processors which can only be processed out-of-place, override this function to give the right behavior.

Parameters

image The image will be copied, actual process happen on copy of image.

Returns: the image processing result, may or may not be the same size of the input image

Reimplemented from EMAN::Processor.

Definition at line 14837 of file processor.cpp.

{
        EMData* imageCp= image -> copy();
        process_inplace(imageCp);
        return imageCp;
}

References copy(), and process_inplace().

◆ process_inplace()

void PruneSkeletonProcessor::process_inplace ( EMData * image )

virtual

To process an image in-place.

For those processors which can only be processed out-of-place, override this function to just print out some error message to remind user call the out-of-place version.

Parameters

image The image to be processed.

Implements EMAN::Processor.

Definition at line 14844 of file processor.cpp.

                                                          {
        // This function is far from optimized, but it works...
 
        int nx = image->get_xsize();
        int ny = image->get_ysize();
        int nz = image->get_zsize();
 
        float threshold=params.set_default("thresh",0);
        int verbose=params.set_default("verbose",0);
        int maxdist=params.set_default("maxdist",3);
        bool returnlength=params.set_default("returnlength",false);
/*
        if (nz > 1) {
                ImageDimensionException("Only 2-D images supported");
        }*/
 
        float *data = image->get_data();
        size_t total_size = (size_t)nx * (size_t)ny * (size_t)nz;
 
        float *data2 = new float[total_size];
        memcpy(data2, data, total_size * sizeof(float));
        int nxy = nx * ny;
        // binarize image and deal with boundary points first
        for (int k=0; k<nz; k++){
                if (verbose>0)
                        printf("layer %d \n",k);
                size_t knxy = (size_t)k * nxy;
                // binarize image first
                for (int j=0; j<ny; j++){
                        int jnx = j * nx;
                        for (int i=0; i<nx; i++){
 
                                if (data[knxy+i+jnx]>threshold)
                                        data[knxy+i+jnx]=1;
                                else
                                        data[knxy+i+jnx]=0;
                        }
                }
 
                float array[9];
                image->to_zero();
 
                // find branch points
                int nbranch=0;
                for (int j=1; j < ny-1; j++) {
                        int jnx = j * nx;
                        for (int i=1; i<nx-1; i++) {
 
                                if (data2[knxy+i+jnx]<=threshold)
                                        continue;
                                int s=0;
                                for (int i2 = i-1; i2 <= i + 1; i2++) {
                                        for (int j2 = j - 1; j2 <= j + 1; j2++) {
                                                array[s++] = data2[knxy+i2 + j2 * nx];
                                        }
                                }
                                int ap=0; // number of transitions from 0 to 1
                                int order[9]={0,1,2,5,8,7,6,3,0};
                                for (int oi=0; oi<8; oi++){
                                        if (array[order[oi]]<=threshold && array[order[oi+1]]>threshold){
                                                ap++;
                                        }
                                }
                                if (ap>2){
                                        data[knxy+i+jnx]=1;
                                        nbranch++;
                                }
                        }
                }
                if (verbose>0)
                        printf("\t %d branch pixels\n",nbranch);
 
                // now, data->branch points, data2->binarized image
 
                // distance to branch point
                for (int j=1; j<ny; j++){
                        int jnx=j*nx;
                        for (int i=0; i<nx; i++){
                                data[knxy+i+jnx]=(1-data[knxy+i+jnx])*(maxdist+1);
                        }
 
                }
                for (int dt=0; dt<maxdist; dt++){
                        for (int j=1; j < ny-1; j++) {
                                int jnx=j*nx;
                                for (int i=1; i<nx-1; i++) {
 
                                        if (data2[knxy+i+jnx]<=threshold)
                                                continue;
                                        if (data[knxy+i+jnx]<=maxdist)
                                                continue;
                                        int db=maxdist; // distance from nearest branch point.
                                        for (int i2=i-1; i2<=i+1; i2++) {
                                                for (int j2=j-1; j2<=j+1; j2++) {
                                                        db=(data[knxy+i2+j2*nx]==dt ? dt : db);
                                                }
                                        }
                                        data[knxy+i+jnx]=db+1;
                                }
                        }
                }
                // now, data->distance to the nearest branch point
                
                if (returnlength==false){
                // mark endpoints for deletion
                int nend=0;
                for (int j=1; j < ny-1; j++) {
                        int jnx=j*nx;
                        for (int i=1; i<nx-1; i++) {
 
                                if (data2[knxy+i+jnx]<=threshold)
                                        continue;
                                if (data[knxy+i+jnx]>maxdist)
                                        continue;
                                int nb=-1;      // number of neighbors
                                for (int i2=i-1; i2<=i+1; i2++) {
                                        for (int j2=j-1; j2<=j+1; j2++) {
                                                nb+=(data2[knxy+i2+j2*nx]>threshold ? 1 : 0);
                                        }
                                }
                                if (nb==1){ // endpoint found
                                        data[knxy+i+jnx]=-data[knxy+i+jnx]; //mark for deletion
                                        data2[knxy+i+jnx]=threshold;
                                        nend++;
                                }
                        }
                }
 
                // remove marked branches
                for (int dt=-maxdist; dt<-1; dt++){
                        for (int j=1; j < ny-1; j++) {
                                int jnx=j*nx;
                                for (int i=1; i<nx-1; i++) {
 
                                        if (data2[knxy+i+jnx]<=threshold)
                                                continue;
                                        if (data[knxy+i+jnx]<=0)
                                                continue;
                                        int rm=0; // delete this pixel
                                        for (int i2=i-1; i2<=i+1; i2++) {
                                                for (int j2=j-1; j2<=j+1; j2++) {
                                                        rm=( data[knxy+i2+j2*nx]==dt ? 1 : rm );
                                                }
                                        }
                                        if (rm>0){
                                                data2[knxy+i+jnx]=threshold;
                                                data[knxy+i+jnx]=dt+1;
                                        }
                                }
                        }
                }
                if (verbose>0)
                        printf("\t %d branches removed\n",nend);
                }
        }
        if (returnlength==false){
                memcpy(data, data2, total_size * sizeof(float));
        }
 
 
        image->update();
        if( data2 )
        {
                delete[]data2;
                data2 = 0;
        }
 
}

References EMAN::Processor::params, and EMAN::Dict::set_default().

Referenced by process().

Member Data Documentation

◆ NAME

const string PruneSkeletonProcessor::NAME = "morph.prune"

static

Definition at line 9650 of file processor.h.

Referenced by get_name().

The documentation for this class was generated from the following files:

Public Member Functions

Static Public Member Functions

Static Public Attributes

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ get_desc()

◆ get_name()

◆ get_param_types()

◆ NEW()

◆ process()

◆ process_inplace()

Member Data Documentation

◆ NAME