#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 6725 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 6752 of file processor.h.
06753 { 06754 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."; 06755 }
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 6730 of file processor.h.
References NAME.
06731 { 06732 return NAME; 06733 }
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 6740 of file processor.h.
References EMAN::EMObject::BOOL, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().
06741 { 06742 TypeDict d; 06743 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"); 06744 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."); 06745 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06746 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."); 06747 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)"); 06748 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"); 06749 return d; 06750 }
static Processor* EMAN::TomoTiltEdgeMaskProcessor::NEW | ( | ) | [inline, static] |
Definition at line 6735 of file processor.h.
06736 { 06737 return new TomoTiltEdgeMaskProcessor(); 06738 }
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 9467 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().
09468 { 09469 bool biedgemean = params.set_default("biedgemean", false); 09470 bool edgemean = params.set_default("edgemean", false); 09471 // You can only do one of these - so if someone specifies them both the code complains loudly 09472 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09473 09474 bool fim = params.set_default("angle_fim", false); 09475 float alt; 09476 if ( fim ) { 09477 Transform* t = (Transform*)image->get_attr("xform.projection"); 09478 Dict d = t->get_params("eman"); 09479 alt = (float) d["alt"]; 09480 if(t) {delete t; t=0;} 09481 } 09482 else alt = params.set_default("angle", 0.0f); 09483 09484 09485 float cosine = cos(alt*M_PI/180.0f); 09486 09487 // Zero the edges 09488 int nx = image->get_xsize(); 09489 int ny = image->get_ysize(); 09490 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09491 09492 float x1_edge_mean = 0.0; 09493 float x2_edge_mean = 0.0; 09494 09495 if ( biedgemean ) 09496 { 09497 float edge_mean = 0.0; 09498 09499 // Accrue the pixel densities on the side strips 09500 for ( int i = 0; i < ny; ++i ) { 09501 edge_mean += image->get_value_at(x_clip, i ); 09502 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09503 } 09504 // Now make it so the mean is stored 09505 edge_mean /= 2*ny; 09506 09507 // Now shift pixel values accordingly 09508 for ( int i = 0; i < ny; ++i ) { 09509 for ( int j = nx-1; j >= nx - x_clip; --j) { 09510 image->set_value_at(j,i,edge_mean); 09511 } 09512 for ( int j = 0; j < x_clip; ++j) { 09513 image->set_value_at(j,i,edge_mean); 09514 } 09515 } 09516 x1_edge_mean = edge_mean; 09517 x2_edge_mean = edge_mean; 09518 } 09519 else if (edgemean) 09520 { 09521 for ( int i = 0; i < ny; ++i ) { 09522 x1_edge_mean += image->get_value_at(x_clip, i ); 09523 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09524 } 09525 x1_edge_mean /= ny; 09526 x2_edge_mean /= ny; 09527 09528 for ( int i = 0; i < ny; ++i ) { 09529 for ( int j = 0; j < x_clip; ++j) { 09530 image->set_value_at(j,i,x1_edge_mean); 09531 } 09532 for ( int j = nx-1; j >= nx - x_clip; --j) { 09533 image->set_value_at(j,i,x2_edge_mean); 09534 } 09535 } 09536 } 09537 else 09538 { 09539 // The edges are just zeroed - 09540 Dict zero_dict; 09541 zero_dict["x0"] = x_clip; 09542 zero_dict["x1"] = x_clip; 09543 zero_dict["y0"] = 0; 09544 zero_dict["y1"] = 0; 09545 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09546 } 09547 09548 int gauss_rad = params.set_default("gauss_falloff", 0); 09549 if ( gauss_rad != 0) 09550 { 09551 // If the gaussian falloff distance is greater than x_clip, it will technically 09552 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09553 // Therefore, there is potential here for (benevolent) unexpected behavior. 09554 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09555 09556 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09557 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09558 float sigma = (float) gauss_rad/gauss_sigma; 09559 09560 GaussianFunctoid gf(sigma); 09561 09562 for ( int i = 0; i < ny; ++i ) { 09563 09564 float left_value = image->get_value_at(x_clip, i ); 09565 float scale1 = left_value-x1_edge_mean; 09566 09567 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09568 float scale2 = right_value-x2_edge_mean; 09569 09570 for ( int j = 1; j < gauss_rad; ++j ) 09571 { 09572 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09573 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09574 } 09575 } 09576 } 09577 09578 image->update(); 09579 }
const string TomoTiltEdgeMaskProcessor::NAME = "tomo.tiltedgemask" [static] |