## CHANGE LOG ##
1.0.0.0
- Initial version
1.1.0.0
- Upgraded to v1B10 of the IM.
- Re-classified this dictionary as a Discipline Dictionary, instead of Mission Dictionary.
- Renamed Surface_Imaging_Parameters to Surface_Imaging, Error_Model_Information to Error_Model,
Geometry_Projection_Parameters to Geometry_Projection, and Pointing_Correction_Parameters to Pointing_Correction.
- Added new attribute to Instrument_Information: ops_instrument_key
1.1.1.0
- Removed Pointing_Correction and its child attributes/classes (moved to IMG)
The Derived_Product_Parameters class contains
attributes used to identify and describe processing performed on
products in order to produce a higher level
product.
The Error_Model class specifies the name of the
error model used, a reference to the algorithm descriptions, and
the parameters needed for that algorithm. The specific set of
values is determined by each individual
missions.
The Error_Model_Parameter class specifies name
and value for a parameter defined by the error model described
by the parent class.
The Error_Pixel class specifies the line and
sample in the image where an error occurred.
The Geometry_Projection describes the geometric
projection or warping the image has undergone. It is not the
intent of this class to describe map projections, but rather
image warps such as linearization (stereo epipolar alignment),
geometric sensor correction, or rubber-sheeting. If present, a
linearization partner image can be referenced using either an
Internal_Reference or External_Reference.
The Image_Identifiers class contains items that
help to identify the image or guide how processing should be
done to the image.
The Instrument_Information class specifies
information about the configuration of the instrument as it
acquired this observation.
Indicates the instrument that is referred to by
the product. This is not the same as the instrument that
acquired the product. For example, on InSight instrument
placement products, it defines which instrument is being
placed.
The Stereo_Product_Parameters class describes
the conditions under which stereo analysis was performed. This
includes items such as the stereo baseline (separation between
the cameras) and what partner image(s) were used for stereo
analysis. If present, stereo partner images can be referenced
using either an Internal_Reference or
External_Reference.
Attributes specific to imaging instruments on
surface missions.
The Vector_Range_Origin class specifies the 3-D
space from which the Range values are measured in a Range RDR.
This will normally be the same as the C point of the camera. It
is expressed in the coordinate system specified by the
Coordinate_Space_Reference class.
This section contains the simpleTypes that provide more constraints
than those at the base data type level. The simpleTypes defined here build on the base data
types. This is another component of the common dictionary and therefore falls within the
common namespace.
The camera_product_id attribute specifies a
numeric identifier assigned by the instrument to this specific
observation.
The camera_product_id_count attribute specifies
the number of times a specific camera_product_id has been
used.
The derived_image_type_name attribute specifies
how to interpret the pixel values in a derived image (or
colloquially, the type of the derived image itself). Valid
values vary per mission depending on the products
produced.
The error_model_name attribute specifies the
method or algorithm used to create the error estimate. Each
mission will define their own set of possible values. Algorithms
will be added over time. The initial value is
MIPL_CONST_DISPARITY_PROJECTED_V1, which means an arbitrary
constant disparity error is assumed (in ERROR_MODEL_PARMS),
which is projected through the camera models to approximate an
error ellipse, which is then projected to the XYZ or
range/crossrange axes depending on the file type.
The geometry_projection_type attribute specifies
how pixels in a file have been reprojected to correct for camera
distortion, linearization, or rubber-sheeting (it is not the
intent of this field to capture map projections). "Raw"
indicates no projection has been done.
The horizon_mask_elevation attribute specifies
the elevation (in degrees) used as the horizontal cutoff in a
mask file that prevents the horizon and sky features in the
image from being processed. If this attribute is not present in
the product label, no horizon mask was used.
TBD
The image_id is an arbitrary string identifier
that is associated with this image. The specific interpretation
of it is mission-dependent, and it need not be unique to this
image. For example, missions may use it as an image counter, a
round-trip token indicating how to process the image, or a
FSW-assigned value identifying the image.
The image_type attribute specifies the type of
image acquired. The intent is to distinguish between different
kinds of image-related data that may differ in how they are
interpreted. Some types are not standard images, but they are
stored in an image structure. Examples include Regular,
Thumbnail, Reference Pixels, Histogram, Row Sum, and Column
Sum.
The instrument_mode_id attribute provides an
instrument-dependent designation of operating mode. This may be
simply a number, letter or code, or a word such as 'normal',
'full resolution', 'near encounter', or 'fixed grating'. These
types may vary by mission so the permissible values should be
set by the mission dictionaries.
The instrument serial number element provides
the manufacturer's serial number assigned to an instrument. This
number may be used to uniquely identify a particular instrument
for tracing its components or determining its calibration
history, for example.
The instrument_type attribute specifies the type
of an instrument, for example IMAGING CAMERA, SPECTROMETER,
IMAGING SPECTROMETER, RADIOMETER, etc.
The instrument_version_number element
identifies the specific model of an instrument used to obtain
data. For example, this keyword could be used to distinguish
between an engineering model of a camera used to acquire test
data, and a flight model of a camera used to acquire science
data during a mission.
The line attribute specifies the line number in
the image.
The linearization_mode attribute specifies what
kind of stereo partner was used to linearize the image (the
process requires two camera models).
The linearization_mode_fov attribute specifies
how the linearized camera model's field of view (FOV) as
constructed (corresponding to the "cahv_fov" parameter in MIPL
software).
The mesh_id attribute specifies which terrain
mesh this image should be automatically included in. This does
not constrain which mesh(es) the image may be included in
outside a pipeline environment.
The mosaic_id attribute specifies which mosaic
this image should be automatically included in. This does not
constrain which mosaic(s) the image may be included in outside a
pipeline environment.
The ops_instrument_key attribute specifies the
identifier or key for the instrument that was used during
operations to look up instrument parameters or
calibration.
The sample attribute specifies the sample number
in the image.
The stereo_baseline_length attribute specifies
the separation between the two cameras used for processing of
the stereo image.
The stereo_match_id attribute specifies which
other image this image matches with for stereo processing. If
used for a mission, the two images making up a stereo pair
should share the same stereo_match_id value.
The x component of a Cartesian position
vector.
The y component of a Cartesian position
vector.
The z component of a Cartesian position
vector.
[
{
"dataDictionary": {
"Title": "PDS4 Data Dictionary" ,
"Version": "1.11.1.0" ,
"Date": "Wed Jun 19 08:56:25 PDT 2019" ,
"Description": "This document is a dump of the contents of the PDS4 Data Dictionary" ,
"PropertyMapDictionary": [
]
}
}
]