Jitter_Correct.m is a MATLAB function that automatically measures and corrects inter-frame jitter in an image sequence to a user-specified precision. In addition, the algorithm dynamically adjusts the image sample size to increase the accuracy of the measurement. The Jitter_Correct.m function takes an image sequence with unknown frame-to-frame jitter and computes the translations of each frame (column and row, in pixels) relative to a chosen reference frame with sub-pixel accuracy. The translations are measured using a Cross Correlation Fourier transformation method in which the relative phase of the two transformed images is fit to a plane. The measured translations are then used to correct the inter-frame jitter of the image sequence. The function also dynamically expands the image sample size over which the cross-correlation is measured to increase the accuracy of the measurement. This increases the robustness of the measurement to variable magnitudes of inter-frame jitte

Palacios, David M.

Waegell, Mordecai J.

NASA Technical Reports Server

NASA Tech Briefs, August 2011 11
Software
Remote Asynchronous Mes-
sage Service Gateway 
The Remote Asynchronous Message
Service (RAMS) gateway is a special-pur-
pose AMS application node that enables
exchange of AMS messages between
nodes residing in different AMS “con-
tinua,” notionally in different geograph-
ical locations. JPL’s implementation of
RAMS gateway functionality is inte-
grated with the ION (Interplanetary
Overlay Network) implementation of
the DTN (Delay-Tolerant Networking)
bundle protocol, and with JPL’s imple-
mentation of AMS itself. RAMS protocol
data units are encapsulated in ION bun-
dles and are forwarded to the neighbor-
ing RAMS gateways identified in the
source gateway’s AMS management in-
formation base. 
Each RAMS gateway has interfaces in
two communication environments: the
AMS message space it serves, and the
RAMS network — the grid or tree of mu-
tually aware RAMS gateways — that en-
ables AMS messages produced in one
message space to be forwarded to other
message spaces of the same venture.
Each gateway opens persistent, private
RAMS network communication chan-
nels to the RAMS gateways of other mes-
sage spaces for the same venture, in
other continua. The interconnected
RAMS gateways use these communica-
tion channels to forward message peti-
tion assertions and cancellations among
themselves. Each RAMS gateway sub-
scribes locally to all subjects that are of
interest in any of the linked message
spaces. On receiving its copy of a mes-
sage on any of these subjects, the RAMS
gateway node uses the RAMS network to
forward the message to every other
RAMS gateway whose message space
contains at least one node that has sub-
scribed to messages on that subject. On
receiving a message via the RAMS net-
work from some other RAMS gateway,
the RAMS gateway node forwards the
message to all subscribers in its own mes-
sage space. 
In this way, the RAMS protocol enables
the free flow of published application
messages across arbitrarily long, deep
space links while protecting efficient use
of those links: only a single copy of any
message is ever transmitted on any
RAMS network communication channel,
no matter how many subscribers will re-
ceive copies when the message reaches
its destination message space. 
Note that the nature of the RAMS
network communication channels de-
pends on the implementation of the
RAMS network. In order to communi-
cate over the RAMS network for a given
venture, each RAMS gateway must know
the RAMS network location — an end-
point in the protocol used to implement
the RAMS network (e.g., the DTN bun-
dle protocol) — at which every other
RAMS gateway for that venture receives
RAMS network traffic. Again, this exten-
sion of the publish/subscribe model to
interplanetary communications is invisi-
ble to application nodes. Application
functionality is unaffected by these de-
tails of network configuration, and the
only effects on behavior are those that
are intrinsic to variability in message
propagation latency. 
This work was done by Shin-Ywan Wang
of Caltech and Scott C. Burleigh of SBAR for
NASA’s Jet Propulsion Laboratory. Further in-
formation is contained in a TSP (see page 1).
This software is available for commercial li-
censing. Please contact Daniel Broderick of
the California Institute of Technology at
danielb@caltech.edu. Refer to NPO-44048.
Automatic Tie Pointer for
In-Situ Pointing Correction 
The MARSAUTOTIE program gener-
ates tie points for use with the Mars
pointing correction software “In-Situ
Pointing Correction and Rover Microlo-
calization,” (NPO-46696) Soft ware Tech
Briefs, Vol. 34, No. 9 (September 2010),
page 18, in a completely automated
manner, with no operator intervention.
It takes the place of MARSTIE, although
MARSTIE can be used to interactively
edit the tie points afterwards. These tie
points are used to create a mosaic whose
seams (boundaries of input images)
have been geometrically corrected to re-
duce or eliminate errors and mis-regis-
trations. The methods used to find ap-
propriate tie points for use in creating a
mosaic are unique, having been de-
signed to work in concert with the
“MARSNAV” program to be most effec-
tive in reducing or eliminating geomet-
ric seams in a mosaic. 
The program takes the input images
and finds overlaps according to the
nominal pointing. It then finds the most
interesting areas using a scene activity
metric. Points with higher scene activity
are more likely to correlate successfully
in the next step. It then uses correlation
techniques to find matching points in
the overlapped image. Finally, it per-
forms a series of steps to reduce the
number of tie points to a manageable
level. These steps incorporate a number
of heuristics that have been devised
using experience gathered by tie point-
ing mosaics manually during MER oper-
ations. The software makes use of the
PIG library as described in “Planetary
Image Geometry Library” (NPO-46658),
NASA Tech Briefs, Vol. 34, No. 12 (Decem-
ber 2010), page 30, so it is multi-mission,
applicable without change to any in-situ
mission supported by PIG. 
The MARSAUTOTIE algorithm is au-
tomated, so it requires no user inter-
vention. Although at the time of this re-
porting it has not been done, this
program should be suitable for integra-
tion into a fully automated mosaic pro-
duction pipeline. 
This work was done by Robert G. Deen of
Caltech for NASA’s Jet Propulsion Labora-
tory. For more information, contact
iaoffice@jpl.nasa.gov.
This software is available for commercial
licensing. Please contact Daniel Broderick of
the California Institute of Technology at
danielb@caltech.edu. Refer to NPO-47083.
Jitter Correction 
Jitter_Correct.m is a MATLAB func-
tion that automatically measures and
corrects inter-frame jitter in an image se-
quence to a user-specified precision. In
addition, the algorithm dynamically ad-
justs the image sample size to increase
the accuracy of the measurement. 
The Jitter_Correct.m function takes
an image sequence with unknown
frame-to-frame jitter and computes the
translations of each frame (column and
row, in pixels) relative to a chosen refer-
ence frame with sub-pixel accuracy. The
translations are measured using a Cross
Correlation Fourier transformation
method in which the relative phase of
the two transformed images is fit to a
plane. The measured translations are
then used to correct the inter-frame jit-
ter of the image sequence.  The function
also dynamically expands the image sam-
https://ntrs.nasa.gov/search.jsp?R=20120006644 2019-08-30T19:52:42+00:00Z
12 NASA Tech Briefs, August 2011
ple size over which the cross-correlation
is measured to increase the accuracy of
the measurement. This increases the ro-
bustness of the measurement to variable
magnitudes of inter-frame jitter. 
This work was done by Mordecai J. Waegell
and David M. Palacios of Caltech for NASA’s
Jet Propulsion Laboratory. For more informa-
tion, contact iaoffice@jpl.nasa.gov.
This software is available for commercial li-
censing. Please contact Daniel Broderick of
the California Institute of Technology at
danielb@caltech.edu. Refer to NPO-47215.
MSLICE Sequencing
MSLICE Sequencing is a graphical
tool for writing sequences and integrat-
ing them into RML files, as well as for
producing SCMF files for uplink. When
operated in a testbed environment, it
also supports uplinking these SCMF files
to the testbed via Chill.
This software features a freeform tex-
tural sequence editor featuring syntax
coloring, automatic content assistance
(including command and argument
completion proposals), complete with
types, value ranges, unites, and descrip-
tions from the command dictionary that
appear as they are typed. The sequence
editor also has a “field mode” that allows
tabbing between arguments and displays
type/range/units/description for each
argument as it is edited. Color-coded
error and warning annotations on prob-
lematic tokens are included, as well as
indications of problems that are not visi-
ble in the current scroll range. “Quick
Fix” suggestions are made for resolving
problems, and all the features afforded
by modern source editors are also in-
cluded such as copy/cut/paste,
undo/redo, and a sophisticated find-
and-replace system optionally using reg-
ular expressions.
The software offers a full XML editor
for RML files, which features syntax col-
oring, content assistance and problem
annotations as above. There is a form-
based, “detail view” that allows structured
editing of command arguments and se-
quence parameters when preferred. The
“project view” shows the user’s “work-
space” as a tree of “resources” (projects,
folders, and files) that can subsequently
be opened in editors by double-clicking.
Files can be added, deleted, dragged-
dropped/copied-pasted between folders
or projects, and these operations are un-
doable and redoable.
A “problems view” contains a tabular
list of all problems in the current work-
space. Double-clicking on any row in the
table opens an editor for the appropriate
sequence, scrolling to the specific line
with the problem, and highlighting the
problematic characters. From there, one
can invoke “quick fix” as described above
to resolve the issue. Once resolved, sav-
ing the file causes the problem to be re-
moved from the problem view.
This work was done by Thomas M. Crockett,
Joseph C. Joswig, Khawaja S. Shams, Jeffrey S.
Norris, and John R. Morris of Caltech for
NASA’s Jet Propulsion Laboratory. For more in-
formation, contact iaoffice@jpl.nasa.gov.
This software is available for commer-
cial licensing. Please contact Daniel
Broderick of the California Institute of
Technology at danielb@caltech.edu.
Refer to NPO-47292.
EOS MLS Level 2 
Data Processing Software
Version 3
This software accepts the EOS MLS cal-
ibrated measurements of microwave radi-
ances products and operational meteoro-
logical data, and produces a set of
estimates of atmospheric temperature
and composition. This version has been
designed to be as flexible as possible. The
software is controlled by a Level 2 Config-
uration File that controls all aspects of
the software: defining the contents of
state and measurement vectors, defining
the configurations of the various forward
models available, reading appropriate a
priori spectroscopic and calibration data,
performing retrievals, post-processing re-
sults, computing diagnostics, and out-
putting results in appropriate files.
In production mode, the software op-
erates in a parallel form, with one in-
stance of the program acting as a master,
coordinating the work of multiple slave
instances on a cluster of computers,
each computing the results for individ-
ual chunks of data. In addition, to do
conventional retrieval calculations and
producing geophysical products, the
Level 2 Configuration File can instruct
the software to produce files of simu-
lated radiances based on a state vector
formed from a set of geophysical prod-
uct files taken as input. Combining both
the retrieval and simulation tasks in a
single piece of software makes it far eas-
ier to ensure that identical forward
model algorithms and parameters are
used in both tasks. This also dramatically
reduces the complexity of the code
maintenance effort.
This work was done by Nathaniel J. Livesey,
W. Van Snyder, William G. Read, Michael J.
Schwartz, Alyn Lambert, Michelle L. Santee,
Honghanh T. Nguyen, Lucien Froidevaux,
Shuhui Wang, Gloria L. Manney, Dong L.
Wu, and Paul A. Wagner of Caltech;
Christina Vuu of Raytheon; and Hugh C.
Pumphrey of the University of Edinburgh for
NASA’s Jet Propulsion Laboratory. For more
information, contact iaoffice@jpl.nasa.gov.
This software is available for commercial li-
censing. Please contact Daniel Broderick of
the California Institute of Technology at
danielb@caltech.edu. Refer to NPO-47221.
DspaceOgre 3D Graphics
Visualization Tool
This general-purpose 3D graphics vi-
sualization C++ tool is designed for visu-
alization of simulation and analysis data
for articulated mechanisms. Examples of
such systems are vehicles, robotic arms,
biomechanics models, and biomolecular
structures. DspaceOgre builds upon the
open-source Ogre3D graphics visualiza-
tion library. It provides additional classes
to support the management of complex
scenes involving multiple viewpoints and
different scene groups, and can be used
as a remote graphics server.
This software provides improved sup-
port for adding programs at the graph-
ics processing unit (GPU) level for im-
proved performance. It also improves
upon the messaging interface it exposes
for use as a visualization server.
This work was done by Abhinandan Jain,
Steven Myint, and Marc I. Pomerantz of
Caltech for NASA’s Jet Propulsion Labora-
tory. For more information, contact iaof-
fice@jpl.nasa.gov.
This software is available for commercial li-
censing. Please contact Daniel Broderick of
the California Institute of Technology at
danielb@caltech.edu. Refer to NPO-47380.


Jitter Correction

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