#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 6643 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 6670 of file processor.h.
06671 { 06672 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."; 06673 }
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 6648 of file processor.h.
References NAME.
06649 { 06650 return NAME; 06651 }
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 6658 of file processor.h.
References EMAN::EMObject::BOOL, EMAN::EMObject::FLOAT, EMAN::EMObject::INT, and EMAN::TypeDict::put().
06659 { 06660 TypeDict d; 06661 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"); 06662 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."); 06663 d.put("angle", EMObject::INT, "The angle that the image is, with respect to the zero tilt image"); 06664 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."); 06665 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)"); 06666 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"); 06667 return d; 06668 }
static Processor* EMAN::TomoTiltEdgeMaskProcessor::NEW | ( | ) | [inline, static] |
Definition at line 6653 of file processor.h.
06654 { 06655 return new TomoTiltEdgeMaskProcessor(); 06656 }
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 9215 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().
09216 { 09217 bool biedgemean = params.set_default("biedgemean", false); 09218 bool edgemean = params.set_default("edgemean", false); 09219 // You can only do one of these - so if someone specifies them both the code complains loudly 09220 if (biedgemean && edgemean) throw InvalidParameterException("The edgemean and biedgemean options are mutually exclusive"); 09221 09222 bool fim = params.set_default("angle_fim", false); 09223 float alt; 09224 if ( fim ) { 09225 Transform* t = (Transform*)image->get_attr("xform.projection"); 09226 Dict d = t->get_params("eman"); 09227 alt = (float) d["alt"]; 09228 if(t) {delete t; t=0;} 09229 } 09230 else alt = params.set_default("angle", 0.0f); 09231 09232 09233 float cosine = cos(alt*M_PI/180.0f); 09234 09235 // Zero the edges 09236 int nx = image->get_xsize(); 09237 int ny = image->get_ysize(); 09238 int x_clip = static_cast<int>( (float) nx * ( 1.0 - cosine ) / 2.0); 09239 09240 float x1_edge_mean = 0.0; 09241 float x2_edge_mean = 0.0; 09242 09243 if ( biedgemean ) 09244 { 09245 float edge_mean = 0.0; 09246 09247 // Accrue the pixel densities on the side strips 09248 for ( int i = 0; i < ny; ++i ) { 09249 edge_mean += image->get_value_at(x_clip, i ); 09250 edge_mean += image->get_value_at(nx - x_clip-1, i ); 09251 } 09252 // Now make it so the mean is stored 09253 edge_mean /= 2*ny; 09254 09255 // Now shift pixel values accordingly 09256 for ( int i = 0; i < ny; ++i ) { 09257 for ( int j = nx-1; j >= nx - x_clip; --j) { 09258 image->set_value_at(j,i,edge_mean); 09259 } 09260 for ( int j = 0; j < x_clip; ++j) { 09261 image->set_value_at(j,i,edge_mean); 09262 } 09263 } 09264 x1_edge_mean = edge_mean; 09265 x2_edge_mean = edge_mean; 09266 } 09267 else if (edgemean) 09268 { 09269 for ( int i = 0; i < ny; ++i ) { 09270 x1_edge_mean += image->get_value_at(x_clip, i ); 09271 x2_edge_mean += image->get_value_at(nx - x_clip-1, i ); 09272 } 09273 x1_edge_mean /= ny; 09274 x2_edge_mean /= ny; 09275 09276 for ( int i = 0; i < ny; ++i ) { 09277 for ( int j = 0; j < x_clip; ++j) { 09278 image->set_value_at(j,i,x1_edge_mean); 09279 } 09280 for ( int j = nx-1; j >= nx - x_clip; --j) { 09281 image->set_value_at(j,i,x2_edge_mean); 09282 } 09283 } 09284 } 09285 else 09286 { 09287 // The edges are just zeroed - 09288 Dict zero_dict; 09289 zero_dict["x0"] = x_clip; 09290 zero_dict["x1"] = x_clip; 09291 zero_dict["y0"] = 0; 09292 zero_dict["y1"] = 0; 09293 image->process_inplace( "mask.zeroedge2d", zero_dict ); 09294 } 09295 09296 int gauss_rad = params.set_default("gauss_falloff", 0); 09297 if ( gauss_rad != 0) 09298 { 09299 // If the gaussian falloff distance is greater than x_clip, it will technically 09300 // go beyond the image boundaries. Thus we clamp gauss_rad so this cannot happen. 09301 // Therefore, there is potential here for (benevolent) unexpected behavior. 09302 if ( gauss_rad > x_clip ) gauss_rad = x_clip; 09303 09304 float gauss_sigma = params.set_default("gauss_sigma", 3.0f); 09305 if ( gauss_sigma < 0 ) throw InvalidParameterException("Error - you must specify a positive, non-zero gauss_sigma"); 09306 float sigma = (float) gauss_rad/gauss_sigma; 09307 09308 GaussianFunctoid gf(sigma); 09309 09310 for ( int i = 0; i < ny; ++i ) { 09311 09312 float left_value = image->get_value_at(x_clip, i ); 09313 float scale1 = left_value-x1_edge_mean; 09314 09315 float right_value = image->get_value_at(nx - x_clip - 1, i ); 09316 float scale2 = right_value-x2_edge_mean; 09317 09318 for ( int j = 1; j < gauss_rad; ++j ) 09319 { 09320 image->set_value_at(x_clip-j, i, scale1*gf((float)j)+x1_edge_mean ); 09321 image->set_value_at(nx - x_clip + j-1, i, scale2*gf((float)j)+x2_edge_mean); 09322 } 09323 } 09324 } 09325 09326 image->update(); 09327 }
const string TomoTiltEdgeMaskProcessor::NAME = "tomo.tiltedgemask" [static] |