svn-gvsig-desktop / branches / v2_0_0_prep / extensions / extRemoteSensing / src / org / gvsig / remotesensing / classification / NoSupervisedClassificationProcess.java @ 26348
History | View | Annotate | Download (13.8 KB)
| 1 |
/* gvSIG. Sistema de Informaci?n Geogr?fica de la Generalitat Valenciana
|
|---|---|
| 2 |
*
|
| 3 |
* Copyright (C) 2006 Instituto de Desarrollo Regional and Generalitat Valenciana.
|
| 4 |
*
|
| 5 |
* This program is free software; you can redistribute it and/or
|
| 6 |
* modify it under the terms of the GNU General Public License
|
| 7 |
* as published by the Free Software Foundation; either version 2
|
| 8 |
* of the License, or (at your option) any later version.
|
| 9 |
*
|
| 10 |
* This program is distributed in the hope that it will be useful,
|
| 11 |
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
| 12 |
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
| 13 |
* GNU General Public License for more details.
|
| 14 |
*
|
| 15 |
* You should have received a copy of the GNU General Public License
|
| 16 |
* along with this program; if not, write to the Free Software
|
| 17 |
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307,USA.
|
| 18 |
*
|
| 19 |
* For more information, contact:
|
| 20 |
*
|
| 21 |
* Generalitat Valenciana
|
| 22 |
* Conselleria d'Infraestructures i Transport
|
| 23 |
* Av. Blasco Iba?ez, 50
|
| 24 |
* 46010 VALENCIA
|
| 25 |
* SPAIN
|
| 26 |
*
|
| 27 |
* +34 963862235
|
| 28 |
* gvsig@gva.es
|
| 29 |
* www.gvsig.gva.es
|
| 30 |
*
|
| 31 |
* or
|
| 32 |
*
|
| 33 |
* Instituto de Desarrollo Regional (Universidad de Castilla La-Mancha)
|
| 34 |
* Campus Universitario s/n
|
| 35 |
* 02071 Alabacete
|
| 36 |
* Spain
|
| 37 |
*
|
| 38 |
* +34 967 599 200
|
| 39 |
*/
|
| 40 |
|
| 41 |
package org.gvsig.remotesensing.classification; |
| 42 |
|
| 43 |
import java.awt.Color; |
| 44 |
import java.io.File; |
| 45 |
import java.io.IOException; |
| 46 |
import java.util.ArrayList; |
| 47 |
import java.util.Arrays; |
| 48 |
|
| 49 |
import org.gvsig.fmap.raster.layers.FLyrRasterSE; |
| 50 |
import org.gvsig.raster.buffer.RasterBuffer; |
| 51 |
import org.gvsig.raster.buffer.WriterBufferServer; |
| 52 |
import org.gvsig.raster.dataset.GeoRasterWriter; |
| 53 |
import org.gvsig.raster.dataset.IBuffer; |
| 54 |
import org.gvsig.raster.dataset.NotSupportedExtensionException; |
| 55 |
import org.gvsig.raster.dataset.io.RasterDriverException; |
| 56 |
import org.gvsig.raster.datastruct.ColorItem; |
| 57 |
import org.gvsig.raster.grid.GridException; |
| 58 |
import org.gvsig.raster.grid.filter.FilterTypeException; |
| 59 |
import org.gvsig.raster.util.RasterToolsUtil; |
| 60 |
import org.gvsig.remotesensing.RemoteSensingUtils; |
| 61 |
|
| 62 |
import com.iver.andami.PluginServices; |
| 63 |
import com.iver.cit.gvsig.exceptions.layers.LoadLayerException; |
| 64 |
import com.iver.cit.gvsig.fmap.layers.FLayer; |
| 65 |
import com.iver.cit.gvsig.project.documents.view.gui.View; |
| 66 |
|
| 67 |
/** NoSupervisedClassificationProcess implementa el m?todo de clasificaci?n de
|
| 68 |
* no supervisada
|
| 69 |
*
|
| 70 |
* @see ClassificationGeneralProcess
|
| 71 |
*
|
| 72 |
* @author Victor Olaya volaya@unex.es
|
| 73 |
* @author Alejandro Mu?oz Sanchez (alejandro.munoz@uclm.es)
|
| 74 |
* @version 15/8/2008
|
| 75 |
*/
|
| 76 |
|
| 77 |
public class NoSupervisedClassificationProcess extends ClassificationGeneralProcess{ |
| 78 |
|
| 79 |
double mean[][]=null; |
| 80 |
double dmax[]= null; |
| 81 |
double dmin[]= null; |
| 82 |
int m_iCells[]=null; |
| 83 |
int m_iThreshold=0; |
| 84 |
int iChangedCells=0; |
| 85 |
|
| 86 |
private static Color[] colors = new Color[] {Color.RED, Color.GREEN, Color.BLUE, Color.YELLOW, Color.MAGENTA, Color.CYAN, |
| 87 |
Color.ORANGE, Color.PINK, Color.WHITE, Color.BLACK}; |
| 88 |
|
| 89 |
|
| 90 |
/** Metodo que recoge los parametros del proceso de clasificacion no supervisada
|
| 91 |
* <LI>rasterSE: Capa de entrada para la clasificaci?n</LI>
|
| 92 |
* <LI> bandList:bandas habilitadas </LI>
|
| 93 |
* <LI>view: vista sobre la que se carga la capa al acabar el proceso</LI>
|
| 94 |
* <LI>filename: path con el fichero de salida</LI>
|
| 95 |
*/
|
| 96 |
public void init() { |
| 97 |
|
| 98 |
rasterSE= (FLyrRasterSE)getParam("layer");
|
| 99 |
view=(View)getParam("view"); |
| 100 |
filename= getStringParam("filename");
|
| 101 |
bandList = (int[])getParam("bandList"); |
| 102 |
numClases = getIntParam("numClases");
|
| 103 |
if (bandList.length == 0 || numClases == 0) |
| 104 |
// no se puede clasificar
|
| 105 |
return;
|
| 106 |
setGrid(); |
| 107 |
rasterResult= RasterBuffer.getBuffer(IBuffer.TYPE_BYTE, inputGrid.getRasterBuf().getWidth(), inputGrid.getRasterBuf().getHeight(), 1, true); |
| 108 |
mean= new double[numClases][inputGrid.getBandCount()]; |
| 109 |
|
| 110 |
dmax=new double [inputGrid.getBandCount()]; |
| 111 |
dmin= new double [inputGrid.getBandCount()]; |
| 112 |
|
| 113 |
// Se completan los datos de
|
| 114 |
for(int i=0; i< inputGrid.getBandCount();i++){ |
| 115 |
inputGrid.setBandToOperate(i); |
| 116 |
try {
|
| 117 |
dmax[i]= inputGrid.getMaxValue(); |
| 118 |
dmin[i]= inputGrid.getMinValue(); |
| 119 |
} catch (GridException e) {
|
| 120 |
// TODO Auto-generated catch block
|
| 121 |
e.printStackTrace(); |
| 122 |
} |
| 123 |
} |
| 124 |
|
| 125 |
double dStep=0.0; |
| 126 |
for (int i = 0; i < inputGrid.getBandCount(); i++){ |
| 127 |
dStep = (dmax[i] - dmin[i]) / ((double) (numClases + 1)); |
| 128 |
for (int j = 0; j < numClases; j++) { |
| 129 |
mean[j][i] = dmin[i] + dStep * (j + 1);
|
| 130 |
} |
| 131 |
} |
| 132 |
m_iThreshold = (int) (inputGrid.getLayerNX()*inputGrid.getNY() * 0.02); |
| 133 |
} |
| 134 |
|
| 135 |
/** Proceso de clasificacion no supervisada*/
|
| 136 |
public void process() throws InterruptedException { |
| 137 |
|
| 138 |
int i;
|
| 139 |
int x,y;
|
| 140 |
|
| 141 |
int iPrevClass=0; |
| 142 |
int iClass=0; |
| 143 |
double dNewMean[][] = null; |
| 144 |
double swap[][]; |
| 145 |
m_iCells = new int [numClases]; |
| 146 |
|
| 147 |
do{
|
| 148 |
Arrays.fill(m_iCells, (byte)0); |
| 149 |
iChangedCells = 0;
|
| 150 |
dNewMean = new double [numClases][inputGrid.getBandCount()]; |
| 151 |
for (i = 0; i < numClases; i++){ |
| 152 |
Arrays.fill(dNewMean[i], 0.0); |
| 153 |
} |
| 154 |
if(inputGrid.getRasterBuf().getDataType()==RasterBuffer.TYPE_BYTE){
|
| 155 |
byte dValues[] = new byte[inputGrid.getBandCount()]; |
| 156 |
for(y=0; y<inputGrid.getNY(); y++){ |
| 157 |
for(x=0; x<inputGrid.getNX(); x++){ |
| 158 |
iPrevClass = rasterResult.getElemByte(y,x,0);
|
| 159 |
inputGrid.getRasterBuf().getElemByte(y,x,dValues); |
| 160 |
iClass = getPixelClassForTypeByte(dValues); |
| 161 |
rasterResult.setElem(y, x, 0,(byte)iClass); |
| 162 |
|
| 163 |
for (i = 0; i < inputGrid.getBandCount(); i++){ |
| 164 |
dNewMean[iClass][i] += dValues[i]&0xff;
|
| 165 |
} |
| 166 |
m_iCells[iClass]++; |
| 167 |
if (iClass != iPrevClass){
|
| 168 |
iChangedCells++; |
| 169 |
} |
| 170 |
} |
| 171 |
} |
| 172 |
} |
| 173 |
|
| 174 |
if(inputGrid.getRasterBuf().getDataType()==RasterBuffer.TYPE_SHORT){
|
| 175 |
short dValues[] = new short[inputGrid.getBandCount()]; |
| 176 |
for(y=0; y<inputGrid.getNY(); y++){ |
| 177 |
for(x=0; x<inputGrid.getNX(); x++){ |
| 178 |
iPrevClass = rasterResult.getElemByte(y,x,0);
|
| 179 |
inputGrid.getRasterBuf().getElemShort(y,x,dValues); |
| 180 |
iClass = getPixelClassForTypeShort(dValues); |
| 181 |
rasterResult.setElem(y, x, 0,(byte)iClass); |
| 182 |
|
| 183 |
for (i = 0; i < inputGrid.getBandCount(); i++){ |
| 184 |
dNewMean[iClass][i] += dValues[i]; |
| 185 |
} |
| 186 |
m_iCells[iClass]++; |
| 187 |
if (iClass != iPrevClass){
|
| 188 |
iChangedCells++; |
| 189 |
} |
| 190 |
} |
| 191 |
} |
| 192 |
} |
| 193 |
|
| 194 |
if(inputGrid.getRasterBuf().getDataType()==RasterBuffer.TYPE_INT){
|
| 195 |
int dValues[] = new int[inputGrid.getBandCount()]; |
| 196 |
for(y=0; y<inputGrid.getNY(); y++){ |
| 197 |
for(x=0; x<inputGrid.getNX(); x++){ |
| 198 |
iPrevClass = rasterResult.getElemByte(y,x,0);
|
| 199 |
inputGrid.getRasterBuf().getElemInt(y,x,dValues); |
| 200 |
iClass = getPixelClassForTypeInt(dValues); |
| 201 |
rasterResult.setElem(y, x, 0,(byte)iClass); |
| 202 |
|
| 203 |
for (i = 0; i < inputGrid.getBandCount(); i++){ |
| 204 |
dNewMean[iClass][i] += dValues[i]; |
| 205 |
} |
| 206 |
m_iCells[iClass]++; |
| 207 |
if (iClass != iPrevClass){
|
| 208 |
iChangedCells++; |
| 209 |
} |
| 210 |
} |
| 211 |
} |
| 212 |
} |
| 213 |
|
| 214 |
if(inputGrid.getRasterBuf().getDataType()==RasterBuffer.TYPE_FLOAT){
|
| 215 |
float dValues[] = new float[inputGrid.getBandCount()]; |
| 216 |
for(y=0; y<inputGrid.getNY(); y++){ |
| 217 |
for(x=0; x<inputGrid.getNX(); x++){ |
| 218 |
iPrevClass = rasterResult.getElemByte(y,x,0);
|
| 219 |
inputGrid.getRasterBuf().getElemFloat(y,x,dValues); |
| 220 |
iClass = getPixelClassForTypeFloat(dValues); |
| 221 |
rasterResult.setElem(y, x, 0,(byte)iClass); |
| 222 |
|
| 223 |
for (i = 0; i < inputGrid.getBandCount(); i++){ |
| 224 |
dNewMean[iClass][i] += dValues[i]; |
| 225 |
} |
| 226 |
m_iCells[iClass]++; |
| 227 |
if (iClass != iPrevClass){
|
| 228 |
iChangedCells++; |
| 229 |
} |
| 230 |
} |
| 231 |
} |
| 232 |
} |
| 233 |
|
| 234 |
if(inputGrid.getRasterBuf().getDataType()==RasterBuffer.TYPE_DOUBLE){
|
| 235 |
double dValues[] = new double[inputGrid.getBandCount()]; |
| 236 |
for(y=0; y<inputGrid.getNY(); y++){ |
| 237 |
for(x=0; x<inputGrid.getNX(); x++){ |
| 238 |
iPrevClass = rasterResult.getElemByte(y,x,0);
|
| 239 |
inputGrid.getRasterBuf().getElemDouble(y,x,dValues); |
| 240 |
iClass = getPixelClassForTypeDouble(dValues); |
| 241 |
rasterResult.setElem(y, x, 0,(byte)iClass); |
| 242 |
|
| 243 |
for (i = 0; i < inputGrid.getBandCount(); i++){ |
| 244 |
dNewMean[iClass][i] += dValues[i]; |
| 245 |
} |
| 246 |
m_iCells[iClass]++; |
| 247 |
if (iClass != iPrevClass){
|
| 248 |
iChangedCells++; |
| 249 |
} |
| 250 |
} |
| 251 |
} |
| 252 |
} |
| 253 |
|
| 254 |
for (i = 0; i <inputGrid.getBandCount(); i++){ |
| 255 |
for (int j = 0; j < numClases; j++) { |
| 256 |
dNewMean[j][i] /= (double)m_iCells[j];
|
| 257 |
} |
| 258 |
} |
| 259 |
|
| 260 |
swap = mean; |
| 261 |
mean= dNewMean; |
| 262 |
dNewMean = swap; |
| 263 |
|
| 264 |
}while (iChangedCells > m_iThreshold);
|
| 265 |
|
| 266 |
writeToFile(); |
| 267 |
} |
| 268 |
|
| 269 |
|
| 270 |
|
| 271 |
public int getPercent() { |
| 272 |
// TODO Auto-generated method stub
|
| 273 |
return 0; |
| 274 |
} |
| 275 |
|
| 276 |
|
| 277 |
public String getLog(){ |
| 278 |
return super.getLog()+"\n\n"+ PluginServices.getText(this,"reclasified_cells")+ iChangedCells +"\n"; |
| 279 |
} |
| 280 |
|
| 281 |
/**
|
| 282 |
* M?todo que implementa el clasificador no supervisado
|
| 283 |
* @param array de tipo byte con los valores del pixel en cada una de las bandas
|
| 284 |
* @return clase a la que pertenece el pixel
|
| 285 |
*/
|
| 286 |
public int getPixelClassForTypeByte(byte[] pixelBandsValues) { |
| 287 |
int iClass = 0; |
| 288 |
double dMinDist = Double.MAX_VALUE; |
| 289 |
double dDist=0; |
| 290 |
double dDif=0; |
| 291 |
|
| 292 |
for (int i = 0; i < numClases; i++) { |
| 293 |
dDist = 0;
|
| 294 |
for (int j = 0; j < pixelBandsValues.length; j++) { |
| 295 |
dDif = mean[i][j] - (pixelBandsValues[j]&0xff);
|
| 296 |
dDist += (dDif* dDif); |
| 297 |
} |
| 298 |
if (dDist < dMinDist){
|
| 299 |
dMinDist = dDist; |
| 300 |
iClass = i; |
| 301 |
} |
| 302 |
} |
| 303 |
return iClass;
|
| 304 |
} |
| 305 |
|
| 306 |
/**
|
| 307 |
* M?todo que implementa el clasificador no supervisado
|
| 308 |
* @param array de tipo double con los valores del pixel en cada una de las bandas
|
| 309 |
* @return clase a la que pertenece el pixel
|
| 310 |
*/
|
| 311 |
public int getPixelClassForTypeShort(short[] pixelBandsValues) { |
| 312 |
int iClass = 0; |
| 313 |
double dMinDist = Double.MAX_VALUE; |
| 314 |
double dDist;
|
| 315 |
double dDif;
|
| 316 |
|
| 317 |
for (int i = 0; i < numClases; i++) { |
| 318 |
dDist = 0;
|
| 319 |
for (int j = 0; j < pixelBandsValues.length; j++) { |
| 320 |
dDif = mean[i][j] - pixelBandsValues[j]; |
| 321 |
dDist += (dDif* dDif); |
| 322 |
} |
| 323 |
if (dDist < dMinDist){
|
| 324 |
dMinDist = dDist; |
| 325 |
iClass = i; |
| 326 |
} |
| 327 |
} |
| 328 |
return iClass;
|
| 329 |
} |
| 330 |
|
| 331 |
/**
|
| 332 |
* M?todo que implementa el clasificador no supervisado
|
| 333 |
* @param array de tipo int con los valores del pixel en cada una de las bandas
|
| 334 |
* @return clase a la que pertenece el pixel
|
| 335 |
*/
|
| 336 |
public int getPixelClassForTypeInt(int[] pixelBandsValues) { |
| 337 |
int iClass = 0; |
| 338 |
double dMinDist = Double.MAX_VALUE; |
| 339 |
double dDist;
|
| 340 |
double dDif;
|
| 341 |
|
| 342 |
for (int i = 0; i < numClases; i++) { |
| 343 |
dDist = 0;
|
| 344 |
for (int j = 0; j < pixelBandsValues.length; j++) { |
| 345 |
dDif = mean[i][j] - pixelBandsValues[j]; |
| 346 |
dDist += (dDif* dDif); |
| 347 |
} |
| 348 |
if (dDist < dMinDist){
|
| 349 |
dMinDist = dDist; |
| 350 |
iClass = i; |
| 351 |
} |
| 352 |
} |
| 353 |
return iClass;
|
| 354 |
} |
| 355 |
|
| 356 |
|
| 357 |
/**
|
| 358 |
* M?todo que implementa el clasificador no supervisado
|
| 359 |
* @param array de tipo float con los valores del pixel en cada una de las bandas
|
| 360 |
* @return clase a la que pertenece el pixel
|
| 361 |
*/
|
| 362 |
public int getPixelClassForTypeFloat(float[] pixelBandsValues) { |
| 363 |
int iClass = 0; |
| 364 |
double dMinDist = Double.MAX_VALUE; |
| 365 |
double dDist;
|
| 366 |
double dDif;
|
| 367 |
|
| 368 |
for (int i = 0; i < numClases; i++) { |
| 369 |
dDist = 0;
|
| 370 |
for (int j = 0; j < pixelBandsValues.length; j++) { |
| 371 |
dDif = mean[i][j] - pixelBandsValues[j]; |
| 372 |
dDist += (dDif* dDif); |
| 373 |
} |
| 374 |
if (dDist < dMinDist){
|
| 375 |
dMinDist = dDist; |
| 376 |
iClass = i; |
| 377 |
} |
| 378 |
} |
| 379 |
return iClass;
|
| 380 |
} |
| 381 |
|
| 382 |
|
| 383 |
/**
|
| 384 |
* M?todo que implementa el clasificador no supervisado
|
| 385 |
* @param array de tipo double con los valores del pixel en cada una de las bandas
|
| 386 |
* @return clase a la que pertenece el pixel
|
| 387 |
*/
|
| 388 |
public int getPixelClassForTypeDouble(double[] pixelBandsValues) { |
| 389 |
int iClass = 0; |
| 390 |
double dMinDist = Double.MAX_VALUE; |
| 391 |
double dDist;
|
| 392 |
double dDif;
|
| 393 |
|
| 394 |
for (int i = 0; i < numClases; i++) { |
| 395 |
dDist = 0;
|
| 396 |
for (int j = 0; j < pixelBandsValues.length; j++) { |
| 397 |
dDif = mean[i][j] - pixelBandsValues[j]; |
| 398 |
dDist += (dDif* dDif); |
| 399 |
} |
| 400 |
if (dDist < dMinDist){
|
| 401 |
dMinDist = dDist; |
| 402 |
iClass = i; |
| 403 |
} |
| 404 |
} |
| 405 |
return iClass;
|
| 406 |
} |
| 407 |
|
| 408 |
|
| 409 |
|
| 410 |
|
| 411 |
public void writeToFile() { |
| 412 |
try{
|
| 413 |
if(filename==null) |
| 414 |
return;
|
| 415 |
GeoRasterWriter grw = null;
|
| 416 |
writerBufferServer = new WriterBufferServer(rasterResult);
|
| 417 |
grw = GeoRasterWriter.getWriter(writerBufferServer, filename, rasterResult.getBandCount(),rasterSE.getAffineTransform(), rasterResult.getWidth(), rasterResult.getHeight(), rasterResult.getDataType(), GeoRasterWriter.getWriter(filename).getParams(), null);
|
| 418 |
grw.dataWrite(); |
| 419 |
grw.setWkt(rasterSE.getWktProjection()); |
| 420 |
grw.writeClose(); |
| 421 |
rasterResult.free(); |
| 422 |
mapContext= view.getModel().getMapContext(); |
| 423 |
mapContext.beginAtomicEvent(); |
| 424 |
FLayer lyr = null;
|
| 425 |
int endIndex = filename.lastIndexOf("."); |
| 426 |
if (endIndex < 0) |
| 427 |
endIndex = filename.length(); |
| 428 |
|
| 429 |
lyr = FLyrRasterSE.createLayer( |
| 430 |
filename.substring(filename.lastIndexOf(File.separator) + 1, endIndex), |
| 431 |
filename, |
| 432 |
view.getMapControl().getProjection() |
| 433 |
); |
| 434 |
|
| 435 |
ArrayList colorItems = new ArrayList(); |
| 436 |
ColorItem colorItem = null;
|
| 437 |
int classValue = 0; |
| 438 |
for (int i=0; i< numClases; i++) { |
| 439 |
colorItem = new ColorItem();
|
| 440 |
if(i<10) |
| 441 |
colorItem.setColor(colors[i]); |
| 442 |
else
|
| 443 |
colorItem.setColor(new Color((float)Math.random(),(float)Math.random(),(float)Math.random())); |
| 444 |
colorItem.setNameClass("class"+i);
|
| 445 |
colorItem.setValue(classValue); |
| 446 |
colorItems.add(colorItem); |
| 447 |
classValue++; |
| 448 |
} |
| 449 |
RemoteSensingUtils.setLeyend(lyr,colorItems); |
| 450 |
mapContext.getLayers().addLayer(lyr); |
| 451 |
mapContext.endAtomicEvent(); |
| 452 |
mapContext.invalidate(); |
| 453 |
|
| 454 |
} catch (NotSupportedExtensionException e) {
|
| 455 |
RasterToolsUtil.messageBoxError(PluginServices.getText(this, "error_writer_notsupportedextension"), this, e); |
| 456 |
} catch (RasterDriverException e) {
|
| 457 |
RasterToolsUtil.messageBoxError(PluginServices.getText(this, "error_writer"), this, e); |
| 458 |
} catch (IOException e) { |
| 459 |
RasterToolsUtil.messageBoxError(PluginServices.getText(this, "error_writer"), this, e); |
| 460 |
}catch (LoadLayerException e) {
|
| 461 |
RasterToolsUtil.messageBoxError("error_cargar_capa", this, e); |
| 462 |
}catch (InterruptedException e) { |
| 463 |
Thread.currentThread().interrupt();
|
| 464 |
} catch (FilterTypeException e) {
|
| 465 |
e.printStackTrace(); |
| 466 |
} |
| 467 |
} |
| 468 |
} |