#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 6642 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 6669 of file processor.h. 06670 { 06671 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."; 06672 }
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Get the processor's name. Each processor is identified by a unique name.
Implements EMAN::Processor. Definition at line 6647 of file processor.h. 06648 {
06649 return NAME;
06650 }
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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 6657 of file processor.h. References EMAN::TypeDict::put(). 06658 { 06659 TypeDict d; 06660 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"); 06661 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."); 06662 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06663 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."); 06664 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)"); 06665 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"); 06666 return d; 06667 }
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Definition at line 6652 of file processor.h. 06653 { 06654 return new TomoTiltEdgeMaskProcessor(); 06655 }
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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 9184 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(). 09185 { 09186 bool biedgemean = params.set_default("biedgemean", false); 09187 bool edgemean = params.set_default("edgemean", false); 09188 // You can only do one of these - so if someone specifies them both the code complains loudly 09189 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09190 09191 bool fim = params.set_default("angle_fim", false); 09192 float alt; 09193 if ( fim ) { 09194 Transform* t = (Transform*)image->get_attr("xform.projection"); 09195 Dict d = t->get_params("eman"); 09196 alt = (float) d["alt"]; 09197 if(t) {delete t; t=0;} 09198 } 09199 else alt = params.set_default("angle", 0.0f); 09200 09201 09202 float cosine = cos(alt*M_PI/180.0f); 09203 09204 // Zero the edges 09205 int nx = image->get_xsize(); 09206 int ny = image->get_ysize(); 09207 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09208 09209 float x1_edge_mean = 0.0; 09210 float x2_edge_mean = 0.0; 09211 09212 if ( biedgemean ) 09213 { 09214 float edge_mean = 0.0; 09215 09216 // Accrue the pixel densities on the side strips 09217 for ( int i = 0; i < ny; ++i ) { 09218 edge_mean += image->get_value_at(x_clip, i ); 09219 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09220 } 09221 // Now make it so the mean is stored 09222 edge_mean /= 2*ny; 09223 09224 // Now shift pixel values accordingly 09225 for ( int i = 0; i < ny; ++i ) { 09226 for ( int j = nx-1; j >= nx - x_clip; --j) { 09227 image->set_value_at(j,i,edge_mean); 09228 } 09229 for ( int j = 0; j < x_clip; ++j) { 09230 image->set_value_at(j,i,edge_mean); 09231 } 09232 } 09233 x1_edge_mean = edge_mean; 09234 x2_edge_mean = edge_mean; 09235 } 09236 else if (edgemean) 09237 { 09238 for ( int i = 0; i < ny; ++i ) { 09239 x1_edge_mean += image->get_value_at(x_clip, i ); 09240 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09241 } 09242 x1_edge_mean /= ny; 09243 x2_edge_mean /= ny; 09244 09245 for ( int i = 0; i < ny; ++i ) { 09246 for ( int j = 0; j < x_clip; ++j) { 09247 image->set_value_at(j,i,x1_edge_mean); 09248 } 09249 for ( int j = nx-1; j >= nx - x_clip; --j) { 09250 image->set_value_at(j,i,x2_edge_mean); 09251 } 09252 } 09253 } 09254 else 09255 { 09256 // The edges are just zeroed - 09257 Dict zero_dict; 09258 zero_dict["x0"] = x_clip; 09259 zero_dict["x1"] = x_clip; 09260 zero_dict["y0"] = 0; 09261 zero_dict["y1"] = 0; 09262 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09263 } 09264 09265 int gauss_rad = params.set_default("gauss_falloff", 0); 09266 if ( gauss_rad != 0) 09267 { 09268 // If the gaussian falloff distance is greater than x_clip, it will technically 09269 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09270 // Therefore, there is potential here for (benevolent) unexpected behavior. 09271 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09272 09273 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09274 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09275 float sigma = (float) gauss_rad/gauss_sigma; 09276 09277 GaussianFunctoid gf(sigma); 09278 09279 for ( int i = 0; i < ny; ++i ) { 09280 09281 float left_value = image->get_value_at(x_clip, i ); 09282 float scale1 = left_value-x1_edge_mean; 09283 09284 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09285 float scale2 = right_value-x2_edge_mean; 09286 09287 for ( int j = 1; j < gauss_rad; ++j ) 09288 { 09289 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09290 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09291 } 09292 } 09293 } 09294 09295 image->update(); 09296 }
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Definition at line 212 of file processor.cpp. |