#include <processor.h>
Inheritance diagram for EMAN::TomoTiltEdgeMaskProcessor:
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 | |
static Processor * | NEW () |
Static Public Attributes | |
static const string | NAME = "tomo.tiltedgemask" |
Classes | |
class | GaussianFunctoid |
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).
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 6680 of file processor.h.
virtual string EMAN::TomoTiltEdgeMaskProcessor::get_desc | ( | ) | const [inline, virtual] |
Get the descrition of this specific processor.
This function must be overwritten by a subclass.
Implements EMAN::Processor.
Definition at line 6707 of file processor.h.
06708 { 06709 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."; 06710 }
virtual string EMAN::TomoTiltEdgeMaskProcessor::get_name | ( | ) | const [inline, virtual] |
Get the processor's name.
Each processor is identified by a unique name.
Implements EMAN::Processor.
Definition at line 6685 of file processor.h.
References NAME.
06686 { 06687 return NAME; 06688 }
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.
Reimplemented from EMAN::Processor.
Definition at line 6695 of file processor.h.
References EMAN::EMObject::BOOL, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().
06696 { 06697 TypeDict d; 06698 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"); 06699 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."); 06700 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06701 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."); 06702 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)"); 06703 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"); 06704 return d; 06705 }
static Processor* EMAN::TomoTiltEdgeMaskProcessor::NEW | ( | ) | [inline, static] |
Definition at line 6690 of file processor.h.
06691 { 06692 return new TomoTiltEdgeMaskProcessor(); 06693 }
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.
image | The image to be processed. |
Implements EMAN::Processor.
Definition at line 9395 of file processor.cpp.
References EMAN::EMData::get_attr(), EMAN::EMData::get_value_at(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), InvalidParameterException, EMAN::Processor::params, EMAN::EMData::process_inplace(), EMAN::Dict::set_default(), EMAN::EMData::set_value_at(), t, and EMAN::EMData::update().
09396 { 09397 bool biedgemean = params.set_default("biedgemean", false); 09398 bool edgemean = params.set_default("edgemean", false); 09399 // You can only do one of these - so if someone specifies them both the code complains loudly 09400 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09401 09402 bool fim = params.set_default("angle_fim", false); 09403 float alt; 09404 if ( fim ) { 09405 Transform* t = (Transform*)image->get_attr("xform.projection"); 09406 Dict d = t->get_params("eman"); 09407 alt = (float) d["alt"]; 09408 if(t) {delete t; t=0;} 09409 } 09410 else alt = params.set_default("angle", 0.0f); 09411 09412 09413 float cosine = cos(alt*M_PI/180.0f); 09414 09415 // Zero the edges 09416 int nx = image->get_xsize(); 09417 int ny = image->get_ysize(); 09418 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09419 09420 float x1_edge_mean = 0.0; 09421 float x2_edge_mean = 0.0; 09422 09423 if ( biedgemean ) 09424 { 09425 float edge_mean = 0.0; 09426 09427 // Accrue the pixel densities on the side strips 09428 for ( int i = 0; i < ny; ++i ) { 09429 edge_mean += image->get_value_at(x_clip, i ); 09430 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09431 } 09432 // Now make it so the mean is stored 09433 edge_mean /= 2*ny; 09434 09435 // Now shift pixel values accordingly 09436 for ( int i = 0; i < ny; ++i ) { 09437 for ( int j = nx-1; j >= nx - x_clip; --j) { 09438 image->set_value_at(j,i,edge_mean); 09439 } 09440 for ( int j = 0; j < x_clip; ++j) { 09441 image->set_value_at(j,i,edge_mean); 09442 } 09443 } 09444 x1_edge_mean = edge_mean; 09445 x2_edge_mean = edge_mean; 09446 } 09447 else if (edgemean) 09448 { 09449 for ( int i = 0; i < ny; ++i ) { 09450 x1_edge_mean += image->get_value_at(x_clip, i ); 09451 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09452 } 09453 x1_edge_mean /= ny; 09454 x2_edge_mean /= ny; 09455 09456 for ( int i = 0; i < ny; ++i ) { 09457 for ( int j = 0; j < x_clip; ++j) { 09458 image->set_value_at(j,i,x1_edge_mean); 09459 } 09460 for ( int j = nx-1; j >= nx - x_clip; --j) { 09461 image->set_value_at(j,i,x2_edge_mean); 09462 } 09463 } 09464 } 09465 else 09466 { 09467 // The edges are just zeroed - 09468 Dict zero_dict; 09469 zero_dict["x0"] = x_clip; 09470 zero_dict["x1"] = x_clip; 09471 zero_dict["y0"] = 0; 09472 zero_dict["y1"] = 0; 09473 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09474 } 09475 09476 int gauss_rad = params.set_default("gauss_falloff", 0); 09477 if ( gauss_rad != 0) 09478 { 09479 // If the gaussian falloff distance is greater than x_clip, it will technically 09480 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09481 // Therefore, there is potential here for (benevolent) unexpected behavior. 09482 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09483 09484 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09485 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09486 float sigma = (float) gauss_rad/gauss_sigma; 09487 09488 GaussianFunctoid gf(sigma); 09489 09490 for ( int i = 0; i < ny; ++i ) { 09491 09492 float left_value = image->get_value_at(x_clip, i ); 09493 float scale1 = left_value-x1_edge_mean; 09494 09495 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09496 float scale2 = right_value-x2_edge_mean; 09497 09498 for ( int j = 1; j < gauss_rad; ++j ) 09499 { 09500 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09501 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09502 } 09503 } 09504 } 09505 09506 image->update(); 09507 }
const string TomoTiltEdgeMaskProcessor::NAME = "tomo.tiltedgemask" [static] |