Main Page | Modules | Namespace List | Class Hierarchy | Alphabetical List | Class List | Directories | File List | Namespace Members | Class Members | File Members

EMAN::TomoTiltEdgeMaskProcessor Class Reference

A processor designed specifically for tomographic tilt series data. More...

#include <processor.h>

Inheritance diagram for EMAN::TomoTiltEdgeMaskProcessor:

[legend]
Collaboration diagram for EMAN::TomoTiltEdgeMaskProcessor:
[legend]
List of all members.

Public Member Functions

virtual void process_inplace (EMData *image)
 To process an image in-place.
virtual string get_name () const
 Get the processor's name.
virtual TypeDict get_param_types () const
 Get processor parameter information in a dictionary.
virtual string get_desc () const
 Get the descrition of this specific processor.

Static Public Member Functions

ProcessorNEW ()

Static Public Attributes

const string NAME = "tomo.tiltedgemask"

Detailed Description

A processor designed specifically for tomographic tilt series data.

This processors masks out 'mass' in tilted images that is not present in the zero-tilt (0 degrees) image. It does this based on the tilt angle. The tilt angle can be extracted from the image metadata (stored as the euler_alt attribute), or it may be specified explicitly (specifying the angle is the default behavior). The masked out regions at both sides of the image are set to 0 by default, but can also be set to the mean of the nearest non-masked data edge (in the y direction), or similarly the mean of both non-masked data edges on either side of the image. A gaussian fall-off is optional (but off by default).

Author:
David Woolford <woolford@bcm.edu>
Date:
01/10/2008
Parameters:
biedgemean Mutually exclusive of edgemean. Experimental. Causes the pixels in the masked out areas to take the average value of both the left and right edge pixel strips
edgemean Mutually exclusive of biedgemean. Masked pixels values assume the mean edge pixel value, independently, for both sides of the image
angle The angle that the image is, with respect to the zero tilt image
angle_fim Read fim as 'from image metadata' - this causes the altitude angle stored in by the image object (i.e. as extracted from the header, as currently stored in memory) to be used as the angle. This overrides the angle argument
gauss_falloff Causes the edge masking to have a smooth Gaussian fall-off - this parameter specifies how many pixels the fall-off will proceed over. Default is 0
gauss_sigma The sigma of the Gaussian function used to smooth the edge fall-off (functional form is exp(-(pixel distance)^2/sigma^2)

Definition at line 6642 of file processor.h.


Member Function Documentation

virtual string EMAN::TomoTiltEdgeMaskProcessor::get_desc  )  const [inline, virtual]
 

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 6669 of file processor.h.

06670                 {
06671                         return "Masks the part of the image which is not present in the 0-tilt image. Masked areas can be 0 or set to the edgemean (of the nearest or both edges). Masked areas can also have a Gaussian fall-off to make the appearance smooth.";
06672                 }

virtual string EMAN::TomoTiltEdgeMaskProcessor::get_name  )  const [inline, virtual]
 

Get the processor's name.

Each processor is identified by a unique name.

Returns:
The processor's name.

Implements EMAN::Processor.

Definition at line 6647 of file processor.h.

06648                 {
06649                         return NAME;
06650                 }

virtual TypeDict EMAN::TomoTiltEdgeMaskProcessor::get_param_types  )  const [inline, virtual]
 

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 6657 of file processor.h.

References EMAN::TypeDict::put().

06658                 {
06659                         TypeDict d;
06660                         d.put("biedgemean", EMObject::BOOL, "Mutually  exclusive of edgemean. Experimental. Causes the pixels in the masked out areas to take the average value of both the left and right edge pixel strips");
06661                         d.put("edgemean", EMObject::BOOL, "Mutually  exclusive of biedgemean. Masked pixels values assume the mean edge pixel value, independently, for both sides of the image.");
06662                         d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image");
06663                         d.put("gauss_falloff",EMObject::INT, "Causes the edge masking to have a smooth Gaussian fall-off - this parameter specifies how many pixels the fall-off will proceed over. Default is 0.");
06664                         d.put("gauss_sigma",EMObject::FLOAT,"The sigma of the Gaussian function used to smooth the edge fall-off (functional form is exp(-(pixel distance)^2/sigma^2)");
06665                         d.put("angle_fim",EMObject::BOOL,"Read fim as 'from image metadata' - this causes the altitude angle stored in by the image object (i.e. as extracted from the header, as currently stored in memory) to be used as the angle. This overrides the angle argument");
06666                         return d;
06667                 }

Processor* EMAN::TomoTiltEdgeMaskProcessor::NEW  )  [inline, static]
 

Definition at line 6652 of file processor.h.

06653                 {
06654                         return new TomoTiltEdgeMaskProcessor();
06655                 }

void TomoTiltEdgeMaskProcessor::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 9184 of file processor.cpp.

References EMAN::EMData::get_attr(), EMAN::Transform::get_params(), EMAN::EMData::get_value_at(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), InvalidParameterException, nx, ny, EMAN::EMData::process_inplace(), EMAN::Dict::set_default(), EMAN::EMData::set_value_at(), t, and EMAN::EMData::update().

09185 {
09186         bool biedgemean = params.set_default("biedgemean", false);
09187         bool edgemean = params.set_default("edgemean", false);
09188         // You can only do one of these - so if someone specifies them both the code complains loudly
09189         if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive");
09190 
09191         bool fim = params.set_default("angle_fim", false);
09192         float alt;
09193         if ( fim ) {
09194                 Transform* t = (Transform*)image->get_attr("xform.projection");
09195                 Dict d = t->get_params("eman");
09196                 alt = (float) d["alt"];
09197                 if(t) {delete t; t=0;}
09198         }
09199         else alt = params.set_default("angle", 0.0f);
09200 
09201 
09202         float cosine = cos(alt*M_PI/180.0f);
09203 
09204         // Zero the edges
09205         int nx = image->get_xsize();
09206         int ny = image->get_ysize();
09207         int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0);
09208 
09209         float x1_edge_mean = 0.0;
09210         float x2_edge_mean = 0.0;
09211 
09212         if ( biedgemean )
09213         {
09214                 float edge_mean = 0.0;
09215 
09216                 // Accrue the pixel densities on the side strips
09217                 for ( int i = 0; i < ny; ++i ) {
09218                         edge_mean += image->get_value_at(x_clip, i );
09219                         edge_mean += image->get_value_at(nx - x_clip-1, i );
09220                 }
09221                 // Now make it so the mean is stored
09222                 edge_mean /= 2*ny;
09223 
09224                 // Now shift pixel values accordingly
09225                 for ( int i = 0; i < ny; ++i ) {
09226                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09227                                 image->set_value_at(j,i,edge_mean);
09228                         }
09229                         for ( int j = 0; j < x_clip; ++j) {
09230                                 image->set_value_at(j,i,edge_mean);
09231                         }
09232                 }
09233                 x1_edge_mean = edge_mean;
09234                 x2_edge_mean = edge_mean;
09235         }
09236         else if (edgemean)
09237         {
09238                 for ( int i = 0; i < ny; ++i ) {
09239                         x1_edge_mean += image->get_value_at(x_clip, i );
09240                         x2_edge_mean += image->get_value_at(nx - x_clip-1, i );
09241                 }
09242                 x1_edge_mean /= ny;
09243                 x2_edge_mean /= ny;
09244 
09245                 for ( int i = 0; i < ny; ++i ) {
09246                         for ( int j = 0; j < x_clip; ++j) {
09247                                 image->set_value_at(j,i,x1_edge_mean);
09248                         }
09249                         for ( int j = nx-1; j >= nx - x_clip; --j) {
09250                                 image->set_value_at(j,i,x2_edge_mean);
09251                         }
09252                 }
09253         }
09254         else
09255         {
09256                 // The edges are just zeroed -
09257                 Dict zero_dict;
09258                 zero_dict["x0"] = x_clip;
09259                 zero_dict["x1"] = x_clip;
09260                 zero_dict["y0"] = 0;
09261                 zero_dict["y1"] = 0;
09262                 image->process_inplace( "mask.zeroedge2d", zero_dict );
09263         }
09264 
09265         int gauss_rad = params.set_default("gauss_falloff", 0);
09266         if ( gauss_rad != 0)
09267         {
09268                 // If the gaussian falloff distance is greater than x_clip, it will technically
09269                 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen.
09270                 // Therefore, there is potential here for (benevolent) unexpected behavior.
09271                 if ( gauss_rad > x_clip ) gauss_rad = x_clip;
09272 
09273                 float gauss_sigma = params.set_default("gauss_sigma", 3.0f);
09274                 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma");
09275                 float sigma = (float) gauss_rad/gauss_sigma;
09276 
09277                 GaussianFunctoid gf(sigma);
09278 
09279                 for ( int i = 0; i < ny; ++i ) {
09280 
09281                         float left_value = image->get_value_at(x_clip, i );
09282                         float scale1 = left_value-x1_edge_mean;
09283 
09284                         float right_value = image->get_value_at(nx - x_clip - 1, i );
09285                         float scale2 = right_value-x2_edge_mean;
09286 
09287                         for ( int j = 1; j < gauss_rad; ++j )
09288                         {
09289                                 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean );
09290                                 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean);
09291                         }
09292                 }
09293         }
09294 
09295         image->update();
09296 }


Member Data Documentation

const string TomoTiltEdgeMaskProcessor::NAME = "tomo.tiltedgemask" [static]
 

Definition at line 212 of file processor.cpp.


The documentation for this class was generated from the following files:
Generated on Fri Apr 30 15:39:29 2010 for EMAN2 by  doxygen 1.3.9.1