mrcImageBilateralFilter - 変更履歴

Tacyas: /* 実行例 */

2019-01-11T02:53:48Z

‎実行例

2014-11-25T22:34:18Z

2014-11-25T22:33:24Z

2014-11-25T22:31:30Z

‎アルゴリズム

2014-11-25T22:29:58Z

‎アルゴリズム

2014-11-25T22:29:34Z

‎アルゴリズム

2014-11-25T22:28:35Z

‎アルゴリズム

2014-11-25T22:27:20Z

‎アルゴリズム

2014-11-25T22:26:32Z

‎アルゴリズム

2014-11-25T22:21:30Z

‎アルゴリズム

@@ 行414: / 行414: @@
 			</td>
 		</tr>
 	</table>
-−
 == 参考資料 ==
 * C. Tomasi and R. Manduchi, Bilateral Filtering for Gray and Color Images, Proceedings of the 1998 IEEE International Conference on Computer Vision, Bombay, India

@@ 行16: / 行16: @@
 ------- linfo.mode : 1
 <math>
-                  W_x(xi,xj) = \frac{1}{1+\frac{|xi-xj|^2}{sigma_{Space}^2} }
+                  W_x(xi,xj) = \frac{1}{1+\frac{|xi-xj|^2}{\sigma_{Space}^2} }
-                  W_I(Ii,Ij) = \frac{1}{1+\frac{|Ii-Ij|^2}{sigma_{Density}^2} }
+                  W_I(Ii,Ij) = \frac{1}{1+\frac{|Ii-Ij|^2}{\sigma_{Density}^2} }
 </math>
@@ 行55: / 行55: @@
 				<td>-sD</td>
 				<td>選択</td>
-				<td>SigmaDensity(float) [ImageAmplitude] : <math>sigma_{Density}</math></td>
+				<td>SigmaDensity(float) [ImageAmplitude] : <math>\sigma_{Density}</math></td>
 				<td>2.0</td>
 			</tr>
@@ 行73: / 行73: @@
 				<td>-sS3</td>
 				<td>選択</td>
-				<td>SigmaSpace 3D (x:float, y:float, z:float) [pixel]: <math>sigma_{Space}</math></td>
+				<td>SigmaSpace 3D (x:float, y:float, z:float) [pixel]: <math>\sigma_{Space}</math></td>
 				<td>1.0 1.0 1.0 </td>
 			</tr>

@@ 行55: / 行55: @@
 				<td>-sD</td>
 				<td>選択</td>
-				<td>SigmaDensity(float) [ImageAmplitude]</td>
+				<td>SigmaDensity(float) [ImageAmplitude] : <math>sigma_{Density}</math></td>
 				<td>2.0</td>
 			</tr>
@@ 行73: / 行73: @@
 				<td>-sS3</td>
 				<td>選択</td>
-				<td>SigmaSpace 3D (x:float, y:float, z:float) [pixel]</td>
+				<td>SigmaSpace 3D (x:float, y:float, z:float) [pixel]: <math>sigma_{Space}</math></td>
 				<td>1.0 1.0 1.0 </td>
 			</tr>

@@ 行11: / 行11: @@
 ------- linfo.mode : 0
 <math>
-                  W_x(x_i,x_j) = exp(-\frac{|x_i-x_j|^2} {2 \sigma_{Space}^2}  ),
+                  W_x(x_i,x_j) = e^{ -\frac{|x_i-x_j|^2} {2 \sigma_{Space}^2}  },
-                  W_I(I_i,I_j) = exp(-\frac{|I_i-I_j|^2} { 2 \sigma_{Density}^2} )
+                  W_I(I_i,I_j) = e^{ -\frac{|I_i-I_j|^2} { 2 \sigma_{Density}^2} }
 </math>
 ------- linfo.mode : 1

@@ 行16: / 行16: @@
 ------- linfo.mode : 1
 <math>
-                  W_x(xi,xj) = \frac{1}{1+\frac{|xi-xj|^2}{sigmaSpace^2} }
+                  W_x(xi,xj) = \frac{1}{1+\frac{|xi-xj|^2}{sigma_{Space}^2} }
-                  W_I(Ii,Ij) = \frac{1}{1+\frac{|Ii-Ij|^2}{sigmaDensity^2} }
+                  W_I(Ii,Ij) = \frac{1}{1+\frac{|Ii-Ij|^2}{sigma_{Density}^2} }
 </math>

@@ 行16: / 行16: @@
 ------- linfo.mode : 1
 <math>
-                  W_x(xi,xj) = 1/(1+|xi-xj|^2/sigmaSpace^2  )
+                  W_x(xi,xj) = \frac{1}{(1+|xi-xj|^2/sigmaSpace^2 }
-                  W_I(Ii,Ij) = 1/(1+|Ii-Ij|^2/sigmaDensity^2)
+                  W_I(Ii,Ij) = \frac{1}{(1+|Ii-Ij|^2/sigmaDensity^2 }
 </math>

@@ 行7: / 行7: @@
 <math>
-f_i=\frac{\sum W(i, j) \cdot I_j}{\sum W(i, j)},
+f_i=\frac{\sum W(i, j) \cdot I_j}{\sum W(i, j)}, where W(i, j)=W_x(x_i, x_j)*W_l(I_i, I_j)
-</math>
-<math>
 , where W(i, j)=W_x(x_i, x_j)*W_l(I_i, I_j)
 </math>
   ------- linfo.mode : 0
 <math>
-                  W_x(xi,xj) = exp(-|xi-xj|^2/2 sigmaSpace^2  )
+                  W_x(x_i,x_j) = exp(-\frac{|x_i-x_j|^2} {2 sigmaSpace^2}  )
-                  W_I(Ii,Ij) = exp(-|Ii-Ij|^2/2 sigmaDensity^2)
+                  W_I(I_i,I_j) = exp(-\frac{|I_i-I_j|^2} { 2 sigmaDensity^2} )
 </math>
   ------- linfo.mode : 1