#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 | |
Processor * | NEW () |
Static Public Attributes | |
const string | NAME = "tomo.tiltedgemask" |
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 6727 of file processor.h.
|
Get the descrition of this specific processor. This function must be overwritten by a subclass.
Implements EMAN::Processor. Definition at line 6754 of file processor.h. 06755 { 06756 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."; 06757 }
|
|
Get the processor's name. Each processor is identified by a unique name.
Implements EMAN::Processor. Definition at line 6732 of file processor.h. 06733 {
06734 return NAME;
06735 }
|
|
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 6742 of file processor.h. References EMAN::TypeDict::put(). 06743 { 06744 TypeDict d; 06745 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"); 06746 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."); 06747 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06748 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."); 06749 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)"); 06750 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"); 06751 return d; 06752 }
|
|
Definition at line 6737 of file processor.h. 06738 { 06739 return new TomoTiltEdgeMaskProcessor(); 06740 }
|
|
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.
Implements EMAN::Processor. Definition at line 9482 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(). 09483 { 09484 bool biedgemean = params.set_default("biedgemean", false); 09485 bool edgemean = params.set_default("edgemean", false); 09486 // You can only do one of these - so if someone specifies them both the code complains loudly 09487 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09488 09489 bool fim = params.set_default("angle_fim", false); 09490 float alt; 09491 if ( fim ) { 09492 Transform* t = (Transform*)image->get_attr("xform.projection"); 09493 Dict d = t->get_params("eman"); 09494 alt = (float) d["alt"]; 09495 if(t) {delete t; t=0;} 09496 } 09497 else alt = params.set_default("angle", 0.0f); 09498 09499 09500 float cosine = cos(alt*M_PI/180.0f); 09501 09502 // Zero the edges 09503 int nx = image->get_xsize(); 09504 int ny = image->get_ysize(); 09505 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09506 09507 float x1_edge_mean = 0.0; 09508 float x2_edge_mean = 0.0; 09509 09510 if ( biedgemean ) 09511 { 09512 float edge_mean = 0.0; 09513 09514 // Accrue the pixel densities on the side strips 09515 for ( int i = 0; i < ny; ++i ) { 09516 edge_mean += image->get_value_at(x_clip, i ); 09517 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09518 } 09519 // Now make it so the mean is stored 09520 edge_mean /= 2*ny; 09521 09522 // Now shift pixel values accordingly 09523 for ( int i = 0; i < ny; ++i ) { 09524 for ( int j = nx-1; j >= nx - x_clip; --j) { 09525 image->set_value_at(j,i,edge_mean); 09526 } 09527 for ( int j = 0; j < x_clip; ++j) { 09528 image->set_value_at(j,i,edge_mean); 09529 } 09530 } 09531 x1_edge_mean = edge_mean; 09532 x2_edge_mean = edge_mean; 09533 } 09534 else if (edgemean) 09535 { 09536 for ( int i = 0; i < ny; ++i ) { 09537 x1_edge_mean += image->get_value_at(x_clip, i ); 09538 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09539 } 09540 x1_edge_mean /= ny; 09541 x2_edge_mean /= ny; 09542 09543 for ( int i = 0; i < ny; ++i ) { 09544 for ( int j = 0; j < x_clip; ++j) { 09545 image->set_value_at(j,i,x1_edge_mean); 09546 } 09547 for ( int j = nx-1; j >= nx - x_clip; --j) { 09548 image->set_value_at(j,i,x2_edge_mean); 09549 } 09550 } 09551 } 09552 else 09553 { 09554 // The edges are just zeroed - 09555 Dict zero_dict; 09556 zero_dict["x0"] = x_clip; 09557 zero_dict["x1"] = x_clip; 09558 zero_dict["y0"] = 0; 09559 zero_dict["y1"] = 0; 09560 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09561 } 09562 09563 int gauss_rad = params.set_default("gauss_falloff", 0); 09564 if ( gauss_rad != 0) 09565 { 09566 // If the gaussian falloff distance is greater than x_clip, it will technically 09567 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09568 // Therefore, there is potential here for (benevolent) unexpected behavior. 09569 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09570 09571 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09572 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09573 float sigma = (float) gauss_rad/gauss_sigma; 09574 09575 GaussianFunctoid gf(sigma); 09576 09577 for ( int i = 0; i < ny; ++i ) { 09578 09579 float left_value = image->get_value_at(x_clip, i ); 09580 float scale1 = left_value-x1_edge_mean; 09581 09582 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09583 float scale2 = right_value-x2_edge_mean; 09584 09585 for ( int j = 1; j < gauss_rad; ++j ) 09586 { 09587 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09588 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09589 } 09590 } 09591 } 09592 09593 image->update(); 09594 }
|
|
Definition at line 212 of file processor.cpp. |