More clarity about examples

docs/book/correlation.tex

@@ -40,18 +40,18 @@ \section{Pre-Processing}
 
 Next, the left and right images are roughly aligned using one of the four
 methods: (1) a homography transform of the right image based on
-automated tie-point measurements, (2) Affine epipolar transform of both
+automated tie-point measurements, (2) an affine epipolar transform of both
 the left and right images (also based on tie-point measurements as earlier),
 the effect of which is equivalent to rotating
 the original cameras which took the pictures, (3) a 3D rotation that achieves
 epipolar rectification {\it(only implemented for Pinhole sessions for
-  missions like MER or K10)} or (4) map-projection of both the left
+  missions like MER or K10 -- see sections \ref{mer:example} and \ref{k10:example})} or (4) map-projection of both the left
 and right images using the \ac{ISIS} \texttt{cam2map} command, or
 through \texttt{mapproject} for Digital Globe and GeoEye images (see
 section \ref{mapproj} for the latter).
 The first three options can be applied automatically by the Stereo
 Pipeline when the \texttt{alignment-method} variable in the
-\texttt{stereo.default} file is set to \texttt{affineepipolar}, 
+\texttt{stereo.default} file is set to \texttt{affineepipolar},
 \texttt{homography}, or \texttt{epipolar}, respectively.
 
 The latter option, running {\tt cam2map}, {\tt cam2map4stereo.py}, or
@@ -365,10 +365,10 @@ \section{Sub-pixel Refinement}
 this sub-pixel algorithm is able to significantly improve upon the
 results to yield a high quality, high resolution result.
 
-Another option when run time is important is \texttt{subpixel-mode 3}: 
-the simple affine correlator.  This is essentially the Bayes EM mode 
+Another option when run time is important is \texttt{subpixel-mode 3}:
+the simple affine correlator.  This is essentially the Bayes EM mode
 with the noise correction features removed in order to decrease the
-required run time.  In data sets with little noise this mode can yield 
+required run time.  In data sets with little noise this mode can yield
 results similar to Bayes EM mode in approximately one fifth the time.
 
 \section{Triangulation}
@@ -467,4 +467,3 @@ \section{Triangulation}
 interpreted as a relative measurement. Where small areas are found
 with high triangulation error came from correlation mistakes and
 large areas of error came from camera model inadequacies.
-

docs/book/examples.tex

@@ -220,6 +220,9 @@ \section{Mars Reconnaissance Orbiter HiRISE}
 the operations carried out by \texttt{hiedr2mosaic.py} can take many
 hours to complete on the very large HiRISE images.
 
+An example of using ASP with HiRISE data is included in the
+\texttt{examples/HiRISE} directory (just type 'make' there).
+
 \subsection{Columbia Hills}
 
 %% \begin{tabular}{ l r c r c}
@@ -289,7 +292,8 @@ \subsection{North Terra Meridiani}
 triangulation of map-projected images is 10x slower than
 non-map-projected images.
 
-This example is distributed in the \texttt{examples/CTX} directory.
+This example is distributed in the \texttt{examples/CTX} directory (type
+'make' there to run it).
 
 \begin{figure}[b!]
 \centering
@@ -389,26 +393,29 @@ \subsubsection*{stereo.default}
 to \texttt{none} when using map-projected imagery. If the images are not
 map-projected, use \texttt{homography} or \texttt{affineepipolar}.
 
-\section{Mars Exploration Rovers MER}
+\section{Mars Exploration Rovers}\label{mer:example}
 
-The MER rovers have several cameras on board and they all seem to have
-a stereo pair. With ASP you are able to process the PANCAM, NAVCAM,
-and HAZCAM camera imagery. ISIS has no telemetry or camera intrinsic
-supports for these images. That however is not a problem as their raw
-imagery contains the cameras' information in JPL's CAHV, CAHVOR, and
-CHAVORE formats.
+The Mars Exploration Rovers (MER) have several cameras on board
+and they all seem to have a stereo pair. With ASP you are able to
+process the PANCAM, NAVCAM, and HAZCAM camera imagery. ISIS has no
+telemetry or camera intrinsic supports for these images. That however is
+not a problem as their raw imagery contains the cameras' information in
+JPL's CAHV, CAHVOR, and CHAVORE formats.
 
 These cameras are all variations of a simple pinhole camera model so
-they are processed with ASP in the \texttt{PINHOLE} session instead of
+they are processed with ASP in the \texttt{Pinhole} session instead of
 the usual \texttt{ISIS}. ASP only supports creating of point
 clouds. \emph{The *-PC.tif is a raw point cloud with the first 3
   channels being XYZ in the rover site's coordinate frame}. We don't
 support the creation of DEMs from these images and that is left as an
 exercise for the user.
 
+An example of using ASP with MER data is included in the
+\texttt{examples/MER} directory (just type 'make' there).
+
 \subsection{PANCAM, NAVCAM, HAZCAM}
 
-All of these cameras are processed the same way. I'll be showing 3D
+All of these cameras are processed the same way. We'll be showing 3D
 processing of the front hazard cams. The only new things in the
 pipeline is the new executable \texttt{mer2camera} along with the use
 of \texttt{alignment-method epipolar}. This example is also provided
@@ -458,6 +465,16 @@ \subsection*{stereo.default}
 \end{Verbatim}
 \end{minipage}\end{center}
 
+\clearpage
+\section{K10}\label{k10:example}
+
+K10 is an Earth-based research rover within the Intelligent
+Robotics Group at NASA Ames, the group ASP developers belong to. The
+cameras on this rover use a simple Pinhole model. The use of ASP with
+these cameras is illustrated in the \texttt{examples/K10} directory
+(just type 'make' there).  Just as for the MER datatset (section
+\ref{mer:example}), only the creation of a point cloud is supported.
+
 \clearpage
 \section{Lunar Reconnaissance Orbiter LROC NAC}
 
@@ -844,7 +861,7 @@ \section{Dawn (FC) Framing Camera}
 
 \begin{center}
 \texttt{FC21A0010191\_11286212239F1T.IMG} and
-\texttt{FC21A0010192\_11286212639F1T.IMG} 
+\texttt{FC21A0010192\_11286212639F1T.IMG}
 \end{center}
 
 which show the Cornelia

docs/book/tutorial.tex

@@ -49,7 +49,7 @@ \section{Preparing the Data}
 pair of Mars Orbital Camera (\ac{MOC}) \citep{1992JGR....97.7699M,2001JGR...10623429M}
 images whose \ac{PDS} Product IDs are M01/00115 and E02/01461.
 This data can be downloaded from the PDS directly, or they can be
-found in the \texttt{data/MOC/} directory of your Stereo Pipeline distribution.
+found in the \texttt{examples/MOC} directory of your Stereo Pipeline distribution.
 
 \subsection{Loading and Calibrating Images using ISIS}