Tawny - Historique des versions

Luc Girod : /* Description */

2019-02-26T13:07:12Z

‎Description

Luc Girod : /* Help */

2019-02-26T13:05:42Z

‎Help

Harlock : formule numbers and some complement in args descriptions.

2017-02-16T03:46:05Z

formule numbers and some complement in args descriptions.

BorisLeroux le 23 février 2016 à 17:02

2016-02-23T17:02:24Z

BorisLeroux le 23 février 2016 à 14:44

2016-02-23T14:44:27Z

Luc Girod le 27 janvier 2016 à 15:34

2016-01-27T15:34:34Z

Luc Girod le 27 janvier 2016 à 15:33

2016-01-27T15:33:01Z

Luc Girod : /* Example */

2016-01-27T10:46:01Z

‎Example

Luc Girod : /* Description */

2016-01-27T10:44:50Z

‎Description

Luc Girod : /* Description */

2016-01-27T10:42:23Z

‎Description

← Version précédente		Version du 26 février 2019 à 13:07
Ligne 11 :		Ligne 11 :

	The radiometry of each image used for the ortho photo will finally be <math>O_i(x, y)P_i(x, y)R(x, y)</math>. Of course for equation (1) and (2), there is much more observations than unknowns and they are solved using least mean square. The user can control the radiometric equalization by specifying the degree of the polynom.		The radiometry of each image used for the ortho photo will finally be <math>O_i(x, y)P_i(x, y)R(x, y)</math>. Of course for equation (1) and (2), there is much more observations than unknowns and they are solved using least mean square. The user can control the radiometric equalization by specifying the degree of the polynom.
		+
		+	If the polynomial correction fail at computing a good radiometric product, the user can deactivate it using ''RadiomEgal=0'' .

	===Syntax===		===Syntax===

@@ Ligne 24 : / Ligne 24 : @@
 Named args :
 *[Name=DEq] INT :: {Degree of equalization (degree of polynoms Oi), Def=1}
 *[Name=DEqXY] Pt2di :: {Degree of equalization, if diff in X and Y}

@@ Ligne 5 : / Ligne 5 : @@
 For the radiometric equalization, Tawny will compute for each individual ortho image <math>O_i</math> a polynom <math>P_i</math> such that, <math>∀(i, j, x, y)</math> where ortho image <math>O_i</math> and <math>O_j</math> are both defined in at the ground coordinates <math>(x, y)</math> we have the relation:
-*<math>O_i(x, y)*P_i(x, y) = O_j(x, y)*P_j(x, y)</math>
+*<math>O_i(x, y)*P_i(x, y) = O_j(x, y)*P_j(x, y)</math>&nbsp;&nbsp;&nbsp;&nbsp;(1)
 The problem with such formula is that it can lead to important drift in radiometry. So there is also a global polynom R that is computed, this polynom is such that:
-*<math>O_i(x, y)*P_i(x, y)*R(x, y) = O_i(x, y)</math>
+*<math>O_i(x, y)*P_i(x, y)*R(x, y) = O_i(x, y)</math>&nbsp;&nbsp;&nbsp;&nbsp;(2)
-The radiometry of each image used for the ortho photo will finally be <math>O_i(x, y)P_i(x, y)R(x, y)</math>. Of course for equation 3.1 and 3.2, there is much more observations than unknowns and they are solved using least mean square. The user can control the radiometric equalization by specifying the degree of the polynom.
+The radiometry of each image used for the ortho photo will finally be <math>O_i(x, y)P_i(x, y)R(x, y)</math>. Of course for equation (1) and (2), there is much more observations than unknowns and they are solved using least mean square. The user can control the radiometric equalization by specifying the degree of the polynom.
 ===Syntax===
@@ Ligne 24 : / Ligne 24 : @@
 Named args :
-*[Name=DEq] INT :: {Degree of equalization (Def=1)}
+*[Name=DEq] INT :: {Degree of equalization (degree of polynoms Oi), Def=1}
 *[Name=DEqXY] Pt2di :: {Degree of equalization, if diff in X and Y}
 *[Name=AddCste] bool :: {Add unknown constant for equalization (Def=false)}
-*[Name=DegRap] INT :: {Degree of rappel to initial values, Def = 0}
+*[Name=DegRap] INT :: {Degree of rappel to initial values (degree of global polynom R), Def = 0}
-*[Name=DegRapXY] Pt2di :: {Degree of rappel to initial values, Def = 0}
+*[Name=DegRapXY] Pt2di :: {Degree of rappel to initial values when different in X and Y, Def = 0}
 *[Name=RGP] bool :: {Rappel glob on physically equalized, Def = true}
 *[Name=DynG] REAL :: {Global Dynamic (to correct saturation problems)}

@@ Ligne 13 : / Ligne 13 : @@
 ===Syntax===
-The global syntax for Tawny is <br>
+The global syntax for Tawny is :
-<code>mm3d Tawny Directory NamedArgs</code>
+<pre>mm3d Tawny Directory NamedArgs</pre>
 ===Help===
-A basic help can be asked with <code> mm3d Tawny -help </code> <br>
+A basic help can be asked with :
+<pre> mm3d Tawny -help </pre>
 Mandatory unnamed args :
@@ Ligne 40 : / Ligne 40 : @@
 ===Example===
-For example in the Mur Saint Martin dataset (or whenever "[[Malt]] Ortho" was used without the "DirMEC" option changed), you can launch : <br>
+For example in the Mur Saint Martin dataset (or whenever "[[Malt]] Ortho" was used without the "DirMEC" option changed), you can launch :
-<code>mm3d Tawny Ortho-MEC-Malt/</code>
+<pre>mm3d Tawny Ortho-MEC-Malt/</pre>

← Version précédente		Version du 23 février 2016 à 14:44
Ligne 1 :		Ligne 1 :
		+	[[Image:picto-liste.png\|25px]] [[Command\|List of commands]]
	==Description==		==Description==
	The simplified tool for generating ortho mosaic is Tawny, it is an interface to the [[Porto]] tool. The use of Tawny is quite simple because it assumes that the data have been correctly prepared and organized during the matching process. Practically this is done when the matching has been made using [[Malt]] and it is recommended to only use Tawny in conjunction with [[Malt]]. In Ortho Mode, Malt has created a set of individual ortho images, associated mask, incidence image, . . . in a directory Ortho-MEC-Malt/		The simplified tool for generating ortho mosaic is Tawny, it is an interface to the [[Porto]] tool. The use of Tawny is quite simple because it assumes that the data have been correctly prepared and organized during the matching process. Practically this is done when the matching has been made using [[Malt]] and it is recommended to only use Tawny in conjunction with [[Malt]]. In Ortho Mode, Malt has created a set of individual ortho images, associated mask, incidence image, . . . in a directory Ortho-MEC-Malt/

@@ Ligne 3 : / Ligne 3 : @@
 The job of Tawny is essentially to merge these data and to optionally do some radiometric equalization.
-For the radiometric equalization, Tawny will compute for each individual ortho image O_i a polynom P_i such that, ∀(i, j, x, y) where ortho image O_i and O_j are both defined in x, y we have the relation:
+For the radiometric equalization, Tawny will compute for each individual ortho image <math>O_i</math> a polynom <math>P_i</math> such that, <math>∀(i, j, x, y)</math> where ortho image <math>O_i</math> and <math>O_j</math> are both defined in at the ground coordinates <math>(x, y)</math> we have the relation:
-* O_i(x, y)*P_i(x, y) = O_j(x, y)*P_j(x, y)
+*<math>O_i(x, y)*P_i(x, y) = O_j(x, y)*P_j(x, y)</math>
 The problem with such formula is that it can lead to important drift in radiometry. So there is also a global polynom R that is computed, this polynom is such that:
-* O_i(x, y)*P_i(x, y)*R(x, y) = O_i(x, y)
+*<math>O_i(x, y)*P_i(x, y)*R(x, y) = O_i(x, y)</math>
 The radiometry of each image used for the ortho photo will finally be O i (x, y)P i (x, y)R(x, y). Of course for equation 3.1 and 3.2, there is much more observations than unknowns and they are solved using least mean square. The user can control the radiometric equalization by specifying the degree of the polynom.