#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 6611 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 6638 of file processor.h.
06639 { 06640 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."; 06641 }
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 6616 of file processor.h.
References NAME.
06617 { 06618 return NAME; 06619 }
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 6626 of file processor.h.
References EMAN::EMObject::BOOL, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().
06627 { 06628 TypeDict d; 06629 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"); 06630 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."); 06631 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06632 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."); 06633 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)"); 06634 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"); 06635 return d; 06636 }
static Processor* EMAN::TomoTiltEdgeMaskProcessor::NEW | ( | ) | [inline, static] |
Definition at line 6621 of file processor.h.
06622 { 06623 return new TomoTiltEdgeMaskProcessor(); 06624 }
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 9277 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().
09278 { 09279 bool biedgemean = params.set_default("biedgemean", false); 09280 bool edgemean = params.set_default("edgemean", false); 09281 // You can only do one of these - so if someone specifies them both the code complains loudly 09282 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09283 09284 bool fim = params.set_default("angle_fim", false); 09285 float alt; 09286 if ( fim ) { 09287 Transform* t = (Transform*)image->get_attr("xform.projection"); 09288 Dict d = t->get_params("eman"); 09289 alt = (float) d["alt"]; 09290 if(t) {delete t; t=0;} 09291 } 09292 else alt = params.set_default("angle", 0.0f); 09293 09294 09295 float cosine = cos(alt*M_PI/180.0f); 09296 09297 // Zero the edges 09298 int nx = image->get_xsize(); 09299 int ny = image->get_ysize(); 09300 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09301 09302 float x1_edge_mean = 0.0; 09303 float x2_edge_mean = 0.0; 09304 09305 if ( biedgemean ) 09306 { 09307 float edge_mean = 0.0; 09308 09309 // Accrue the pixel densities on the side strips 09310 for ( int i = 0; i < ny; ++i ) { 09311 edge_mean += image->get_value_at(x_clip, i ); 09312 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09313 } 09314 // Now make it so the mean is stored 09315 edge_mean /= 2*ny; 09316 09317 // Now shift pixel values accordingly 09318 for ( int i = 0; i < ny; ++i ) { 09319 for ( int j = nx-1; j >= nx - x_clip; --j) { 09320 image->set_value_at(j,i,edge_mean); 09321 } 09322 for ( int j = 0; j < x_clip; ++j) { 09323 image->set_value_at(j,i,edge_mean); 09324 } 09325 } 09326 x1_edge_mean = edge_mean; 09327 x2_edge_mean = edge_mean; 09328 } 09329 else if (edgemean) 09330 { 09331 for ( int i = 0; i < ny; ++i ) { 09332 x1_edge_mean += image->get_value_at(x_clip, i ); 09333 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09334 } 09335 x1_edge_mean /= ny; 09336 x2_edge_mean /= ny; 09337 09338 for ( int i = 0; i < ny; ++i ) { 09339 for ( int j = 0; j < x_clip; ++j) { 09340 image->set_value_at(j,i,x1_edge_mean); 09341 } 09342 for ( int j = nx-1; j >= nx - x_clip; --j) { 09343 image->set_value_at(j,i,x2_edge_mean); 09344 } 09345 } 09346 } 09347 else 09348 { 09349 // The edges are just zeroed - 09350 Dict zero_dict; 09351 zero_dict["x0"] = x_clip; 09352 zero_dict["x1"] = x_clip; 09353 zero_dict["y0"] = 0; 09354 zero_dict["y1"] = 0; 09355 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09356 } 09357 09358 int gauss_rad = params.set_default("gauss_falloff", 0); 09359 if ( gauss_rad != 0) 09360 { 09361 // If the gaussian falloff distance is greater than x_clip, it will technically 09362 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09363 // Therefore, there is potential here for (benevolent) unexpected behavior. 09364 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09365 09366 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09367 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09368 float sigma = (float) gauss_rad/gauss_sigma; 09369 09370 GaussianFunctoid gf(sigma); 09371 09372 for ( int i = 0; i < ny; ++i ) { 09373 09374 float left_value = image->get_value_at(x_clip, i ); 09375 float scale1 = left_value-x1_edge_mean; 09376 09377 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09378 float scale2 = right_value-x2_edge_mean; 09379 09380 for ( int j = 1; j < gauss_rad; ++j ) 09381 { 09382 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09383 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09384 } 09385 } 09386 } 09387 09388 image->update(); 09389 }
const string TomoTiltEdgeMaskProcessor::NAME = "tomo.tiltedgemask" [static] |