Differences between revisions 58 and 59

lithos

Aligns maplets to the current shape model and will provide slight changes to the shape (stored in MAPFILES).

Lithos is the key for SPC. It works on a single landmark, which defined the associated maplet. This landmark must be created (i.e. fully defined) and all the images that include it must be shifted so that everything is aligned. Once those are done, you can calculate the topography which includes identify other maps that overlap, creating a template, and then solving the whole system.

Lithos and LithosP are used by make_script(P) for batch processing. The mark_script program will create a script for each landmark that you will process, which is taken as input (e.g. lithos < LAND01.IIN > LAND01.OOT)

Build a template

Option 0

Align images

Option 1

Calculate topography

Option 2

Housekeeping functions

Option c - create a landmark
Option i - "input" a landmark. Basically, start using the landmark.
Option e - eliminate
- - Good values to use, "0 40 0.2 0.2 0 2"
- - Based on: Input INVLIM, SLIM, CLIM, ILIM, RSMN, RSMX

Input - optional file

aaa.INN - a script that sends batch commands

Input - stdin

Basic steps
Create a landmark, "C"
Input a landmark (really that is selecting it for use), "I"
Creating a template (the virtual idea of the topography and albedo based on the maplets), 0, 0, 40
Aligning the maplets (0 for auto, 1 for manual, 2 for move all maplets, 3 to align to a specific maplet)
Update and save, "U 1"

Output

aaa.OOT
landmark and map files
LMRK_DISPLAY0.pgm
LMRK_DISPLAY1.pgm -- stretched version
slopeb.pgm - shows slope both in x and y

PowerPoint Notes

Description

Creates landmark files, determines landmark topography (MAPFILE), and locates landmark center in images

Inputs

INIT_LITHOS.TXT
SUMFILESR
SPC IMG
NOMINALS
SPICE
MAPLETSL

Outputs

SUMFILESL
LMKFILESL
MAPLETSL
LMRKLIST.TXT

Process Overview

Maplet Definition

3D topography & relative albedo model of a portion of the surface
- Control vector V from body center to origin of local coordinate system
- Local coordinate system axes ui(i=1, 3) with u3 normal to the local surface
- 2-D grid, typically 99x99 pixels with positions x=(x1, x2) relative to origin
Local heights h(x1, x2) and relative albedos a(x1, x2) at each grid point
Camera coordinate system ci(i=1, 3) and S/C position W
Maplet control point not tied to a specific surface feature
Maplet pixel scale not tied to specific image resolution

Specifying a Maplet

Maplets specified by selecting control point based on
- (1) pixel, line position of a given image
- (2) Lat/Lon
- (3) Relative to local coordinates (x1, x2) of existing nearby maplet
Setting scale (km/pix), #pixels/row
(1) => (p, l) mapped onto surface, control vector V determined by bi-linear interpolation from heights of nearest 4 vectors of a-priori topography. Same with (2), (3)
Construct local tangent plane and set u3 normal to local surface
Interpolate heights from a-priori topography to maplet pixels => h(x1,x2)

Picture Description

Left: empty placeholder maplet wrt which we select maplet centers
Right: Control point distribution on Enceladus based on Lat/Lon

Extracting Image Data

Automatically find all images that contain area of given maplet, whole or in part, based on the a-priori geometry
Automatically filter candidate images based on number of criteria such as;
- Resolution ratio between maplet/image scale (typically 1/3 - x3)
- Range of off-nadir view angles at maplet center (typically up to 60 )
- Brightness threshold of portion of image extract
Any number of images (3 - few hundreds) used
Maplet pixels projected in focal plane and image brightness resampled on maplet pixels via bilinear interpolation
Dark & invisible pixels are ignored & pixel brightness rescaled

Extracting Image Data With No A-Priori Topo Information

Zero initial albedo
Flat slopes from smooth sphere a-priori shape
Predicted brightness is a near uniform value across template

Extracting Image Data With A-Priori Topo Information

Resampled images at 175 m/pix projected on existing low-res topography at 500 m/pix
Predicted brightness is derived from that low resolution topography

Menu Description

LANDMARK/MAPLET CONSTRUCTION

0. Find template
1. Align landmarks
2. Find heights
O. Attach map to maps or limbs

LANDMARK/MAPLET I/O AND CREATION

I. Input landmark
- Input 6 character name
U. Update landmark files
C. Create new landmark
- Input 6 character landmark name
R. Replicate or Rename landmark
- Input 6 character old landmark name
- Input 6 character new landmark name
- Delete old landmark? (y/n)
S. Change scale, qsz or orientation
G. Turn on rename

ADJUST INPUT DATA AND NOMINALS

N. Find normal
1. Normal from radius vector
2. Normal from heights
3. Normal from shape
4. Normal from stereo
V. Find V, Z or PTG
1. V from Z and pointing
2. Z from V and pointing
3. PTG/SCOBJ from Z and V (selected image)
4. PTG/SCOBJ from Z and V (current images)
A. Reset albedo or slopes
M. Get heights from shape model

B. Get heights from surrounding map

List possibilities? (y/n)

if y

CP0002    0.0500    1.0000
CQ0004    0.0500    1.0000
CQ0008    0.0250    1.0000
CQ0009    0.0250    0.9822
CQ0017    0.0120    0.9153
DP0002    0.0500    0.8923
......    ......    ......

Input a 6-character name.
0 to cancel

X. Turn on/off extract filter. Tol = 0.050

DELETE, ELIMINATE OR IGNORE FILES

D. Delete or Disconnect landmark
E. Eliminate pictures from landmark
- c. Continue
- a. Auto remove
- n. Auto remove (new pictures)
- m. Manual remove
- p. Check peripheral visibility
- o. Remove no-correlation pix
- t. Auto change topo flag
- For a, n, & t Input INVLIM, SLIM, CLIM, RSMN, RSMX
P. Picture status
1. Tuck or untuck
2. Toss
L. Turn off picture restriction

INFORMATION AND DISPLAY

F. Find maplets containing surface point
Z. Use zoom display
H. Hide screen output

Example of Finding a Tempalte

../LITHOSPHERE/LITHOS.e

i
CQ0082 - input landmark
n - no new pictures (auto)
n - no new pictures (manual
x - turn on extract filter
.025 - filter setting
0 - find template

CQ0082
Lat =    34.721
Lon =    30.609
Rad =     7.830

    k    chi    lambda    phi    res

    1   0.982   1.657   0.000   0.013      
    2   0.980   1.758   0.020   0.013      
    3   0.978   1.894   0.000   0.013      
    . . .
   19   0.975   1.566   0.000   0.013      
   20   0.890   0.564   0.388   0.011     
   21   0.967   1.200   0.106   0.006      
   22   0.974   1.467   0.039   0.006 

Picture to toggle
 a use all
 b use registered
 c use correlated
 0 end/continue
 q Quit

a use all pics (find template will then be repeated)
0 find template

CQ0082
Lat =    34.721
Lon =    30.609
Rad =     7.830
    1   0.982   1.657   0.000   0.013      
    2   0.980   1.758   0.020   0.013      
    3   0.978   1.894   0.000   0.013      
    . . .
   19   0.975   1.566   0.000   0.013      
   20   0.890   0.564   0.388   0.011    
   21   0.967   1.200   0.106   0.006      
   22   0.974   1.467   0.039   0.006 

Picture to toggle
 a use all
 b use registered
 c use correlated
 0 end/continue
 q Quit

0 - find template
40 - entering number of iterations

 rms brightness residual =     0.0263363486
 rms brightness residual =     0.025349268
 rms brightness residual =     0.0248495566
 rms brightness residual =     0.0245736285
 rms brightness residual =     0.0244101752
 . . .
 rms brightness residual =     0.0237731646
 rms brightness residual =     0.0237679522
 rms brightness residual =     0.0237629545
 rms brightness residual =     0.0237581461
 rms brightness residual =     0.023753511

slope sigma =   0.20933789259641114     

  -0.13586   0.16231  -0.42437   0.16636  -0.21634   0.21424   
      
gc tmpl.pgm

(slope sigma above is not correct for example landmark)

gc LMRK_DISPLAY1.pgm

z (zoom display)

gc LMRK_DISPLAY1.pgm

Useful when hundreds of images are displayed
We have used the brightness variations in 22 pictures at varying geometries and illuminations to solve for a “template”. This is a slope/albedo map of the landmark.
This only works if the landmarks are roughly aligned (Option 1) and the map normal (Option N) is roughly correct and the pointings and s/c positions (see REGISTER) are roughly correct.

Example of Aligning Landmarks

1 - aligning landmarks

  0. Auto align
  1. Individual shift
  2. Global shift
  3. Align with picture
  4. Align with gradient

0 - auto align

enter spacing

1 - value selected for spacing (larger values do a dumber correlation over a wider range)

  1   M0130996017        -0.001     0.006     0.983 +++++
  2   M0130996102         0.013    -0.008     0.980 +++++
  3   M0130996187         0.012     0.003     0.979 +++++
  4   M0131278391        -0.052    -0.011     0.972 +++++
  5   M0131278655         0.010    -0.005     0.979 +++++
  6   M0131278919         0.006     0.004     0.977 +++++
  7   M0131279183         0.002     0.001     0.983 +++++
  8   M0131279711         0.014    -0.011     0.977 +++++
  9   M0132106609        -0.002     0.003     0.944 +++++
 10   M0132106706         0.007     0.045     0.896 +++++
 11   M0132225961         0.012     0.003     0.960 +++++
 12   M0134213600         0.012     0.014     0.952 +++++
 13   M0135729214        -0.001     0.000     0.983 +++++
 14   M0135844895         0.029    -0.002     0.934 +++++
 15   M0135844957         0.006     0.011     0.960 +++++
 16   M0137457715         0.020     0.009     0.979 +++++
 17   M0138840893        -0.002     0.005     0.979 +++++
 18   M0140968493         0.004     0.008     0.981 +++++
 19   M0143092151        -0.006    -0.003     0.976 +++++
 20   M0132106900         0.000     0.007     0.890 +++++
 21   M0138580606         0.010     0.012     0.967 +++++
 22   M0138580916         0.004    -0.003     0.974 +++++

n - new spacing? (y/n)

 0.  continue. 
 1.  halve shifts.     
 2.  quarter shifts.

0 - continue
y - update landmark pixel locations? (y/n)
1 -

Example of Finding Heights

Example of Attaching Map to Maps or Limbs

CategoryPrograms