#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 6470 of file processor.h.
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Get the descrition of this specific processor. This function must be overwritten by a subclass.
Implements EMAN::Processor. Definition at line 6497 of file processor.h. 06498 { 06499 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."; 06500 }
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Get the processor's name. Each processor is identified by a unique name.
Implements EMAN::Processor. Definition at line 6475 of file processor.h. 06476 {
06477 return NAME;
06478 }
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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 6485 of file processor.h. References EMAN::TypeDict::put(). 06486 { 06487 TypeDict d; 06488 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"); 06489 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."); 06490 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06491 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."); 06492 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)"); 06493 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"); 06494 return d; 06495 }
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Definition at line 6480 of file processor.h. 06481 { 06482 return new TomoTiltEdgeMaskProcessor(); 06483 }
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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 9230 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(). 09231 { 09232 bool biedgemean = params.set_default("biedgemean", false); 09233 bool edgemean = params.set_default("edgemean", false); 09234 // You can only do one of these - so if someone specifies them both the code complains loudly 09235 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09236 09237 bool fim = params.set_default("angle_fim", false); 09238 float alt; 09239 if ( fim ) { 09240 Transform* t = (Transform*)image->get_attr("xform.projection"); 09241 Dict d = t->get_params("eman"); 09242 alt = (float) d["alt"]; 09243 if(t) {delete t; t=0;} 09244 } 09245 else alt = params.set_default("angle", 0.0f); 09246 09247 09248 float cosine = cos(alt*M_PI/180.0f); 09249 09250 // Zero the edges 09251 int nx = image->get_xsize(); 09252 int ny = image->get_ysize(); 09253 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09254 09255 float x1_edge_mean = 0.0; 09256 float x2_edge_mean = 0.0; 09257 09258 if ( biedgemean ) 09259 { 09260 float edge_mean = 0.0; 09261 09262 // Accrue the pixel densities on the side strips 09263 for ( int i = 0; i < ny; ++i ) { 09264 edge_mean += image->get_value_at(x_clip, i ); 09265 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09266 } 09267 // Now make it so the mean is stored 09268 edge_mean /= 2*ny; 09269 09270 // Now shift pixel values accordingly 09271 for ( int i = 0; i < ny; ++i ) { 09272 for ( int j = nx-1; j >= nx - x_clip; --j) { 09273 image->set_value_at(j,i,edge_mean); 09274 } 09275 for ( int j = 0; j < x_clip; ++j) { 09276 image->set_value_at(j,i,edge_mean); 09277 } 09278 } 09279 x1_edge_mean = edge_mean; 09280 x2_edge_mean = edge_mean; 09281 } 09282 else if (edgemean) 09283 { 09284 for ( int i = 0; i < ny; ++i ) { 09285 x1_edge_mean += image->get_value_at(x_clip, i ); 09286 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09287 } 09288 x1_edge_mean /= ny; 09289 x2_edge_mean /= ny; 09290 09291 for ( int i = 0; i < ny; ++i ) { 09292 for ( int j = 0; j < x_clip; ++j) { 09293 image->set_value_at(j,i,x1_edge_mean); 09294 } 09295 for ( int j = nx-1; j >= nx - x_clip; --j) { 09296 image->set_value_at(j,i,x2_edge_mean); 09297 } 09298 } 09299 } 09300 else 09301 { 09302 // The edges are just zeroed - 09303 Dict zero_dict; 09304 zero_dict["x0"] = x_clip; 09305 zero_dict["x1"] = x_clip; 09306 zero_dict["y0"] = 0; 09307 zero_dict["y1"] = 0; 09308 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09309 } 09310 09311 int gauss_rad = params.set_default("gauss_falloff", 0); 09312 if ( gauss_rad != 0) 09313 { 09314 // If the gaussian falloff distance is greater than x_clip, it will technically 09315 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09316 // Therefore, there is potential here for (benevolent) unexpected behavior. 09317 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09318 09319 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09320 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09321 float sigma = (float) gauss_rad/gauss_sigma; 09322 09323 GaussianFunctoid gf(sigma); 09324 09325 for ( int i = 0; i < ny; ++i ) { 09326 09327 float left_value = image->get_value_at(x_clip, i ); 09328 float scale1 = left_value-x1_edge_mean; 09329 09330 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09331 float scale2 = right_value-x2_edge_mean; 09332 09333 for ( int j = 1; j < gauss_rad; ++j ) 09334 { 09335 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09336 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09337 } 09338 } 09339 } 09340 09341 image->update(); 09342 }
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Definition at line 207 of file processor.cpp. |