Working with Mars Viking Orbiter Data
From Isis Workshop
[edit] About the Viking Mission to Mars
[edit] The Viking Orbiter Mission (1975 to 1980)
NASA's Viking Mission to Mars was composed of two spacecraft, Viking 1 and Viking 2, each consisting of an orbiter and a lander. The primary mission objectives were to obtain high resolution images of the Martian surface, characterize the structure and composition of the atmosphere and surface, and search for evidence of life.
Viking 1 was launched on August 20, 1975 and arrived at Mars on June 19, 1976. The first month of orbit was devoted to imaging the surface to find appropriate landing sites for the Viking Landers. On July 20, 1976 the Viking 1 Lander separated from the Orbiter and touched down at Chryse Planitia. Viking 2 was launched September 9, 1975 and entered Mars orbit on August 7, 1976. The Viking 2 Lander touched down at Utopia Planitia on September 3, 1976.
The Orbiters imaged the entire surface of Mars at a resolution of 150 to 300 meters, and selected areas at 8 meters. The Viking 2 Orbiter was powered down on July 25, 1978 after 706 orbits, and the Viking 1 Orbiter on August 17, 1980, after over 1400 orbits.
[edit] The Viking Visual Imaging Subsystem Instrument
The Viking Visual Imaging Subsystem (VIS) on the orbiter consisted of twin high-resolution, slow-scan television framing cameras mounted on the scan platform of each orbiter with the optical axes offset by 1.38 deg. Each of the two identical cameras on each orbiter had mechanical shutters; a 475-mm focal length telescope; a 37-mm diameter vidicon (video camera tube), the central section of which was scanned in a raster (i.e. image) format of 1056 lines by 1182 samples.
A filter wheel between the lens and shutter held six color filter positions: blue (0.35 to 0.53 micrometers), minus-blue (0.48 - 0.70), violet (0.35 - 0.47), green (0.50 - 0.60), red (0.55 - 0.70), and clear (no filter). The footprint of each image covers roughly 40 x 44 km, acquired from an altitude of 1500 km. The configuration of the cameras provided overlapping, wide-swath coverage of the surface. Each pixel was digitized as a 7-bit number (0 to 127) stored in the onboard tape-recorder, and later transmitted to Earth and converted to an 8-bit number by multiplying by 2.
[edit] Related Resources & References
[edit] Processing Viking Orbiter VIS Data
- Level 0: Data Ingestion
Acquire Viking VIS data from one of numerous sources, import it into Isis, and initialize it with SPICE information.
- Level 1: Noise Removal and Radiometric Calibration
Remove the salt-and-pepper noise, reseau marks, and missing track noise in the data, then radiometrically calibrate the image data so the DNs represent reflectance (ranging from 0 to 1).
- Level 2 - Projection
Geodetic corrections are performed and the images projected to a map projection.
- Level 3 – Photometric Correction and Enhancement
The effect of sun angle on the image is corrected, and the images are tone matched.
- Level 4 – Building a Mosaic
A seamless mosaic is created.
[edit] Level 0 Processing - Data Ingestion
This is the starting point for the production of a Viking mosaic. The steps within the level zero processing provide the gateway into Isis processing. Running the following applications will ingest the Engineering Data Record (EDR) and place necessary information into the labels of the image. Viking Obiter information has been around for quite awhile so problems with the dataset have been discovered and accounted for, allowing this process to run smoothly.
[edit] Acquiring Viking Orbiter Data
- Planetary Data System: The Planetary Data System (PDS) Planetary Image Atlas, hosted by the Jet Propulsion Laboratory and USGS Astrogeology Research Program.
- USGS Planetary GIS Web Server: The USGS Planetary GIS Web Server allows a user to view Viking footprints and verify image coverage.
- JMARS Geographic Information System: The JMARS Geographic Information System (GIS), offered by the Arizona State University's Mars Spaceflight Facility.
Hint: When searching for Viking orbiter data that covers your area of interest, it can be useful to widen you search area by as much as five degrees to each value in your latitude and longitude search values. The camera pointing for Viking images may be off by as much as a half frame so expanding your search will help insure that you get all the images that were acquired for that area.
[edit] Related Resources
- PDS Imaging Node: Online access to Viking mission data volumes
- Planetary Image Atlas - graphical searching or browse by volume
- JMARS Geographic Information System (GIS)
- Image Extent Information: Index files containing latitude and longitude boundaries for Viking images
[edit] Data Acquisition Tool: Planetary Image Atlas
The Planetary Data System (PDS) Imaging Node houses data from several planetary missions, and offers a variety of methods for accessing their holdings. For now we will concentrate on acquiring Viking Orbiter data.
Search The PDS Planetary Image Atlas provides a Product Search search tool to interrogate the collection of Viking Orbiter Imagery. This tool lets us query information about each image and ignores the data that we have no interest in. A good way to reduce the number of images to look at is by defining an area of interest with latitude and longitude ranges. You can also restrict the search by choosing a minimum and maximum resolution. Remember to keep in mind the coordinate system (areographic west for Viking) and units (generally kilometers for distances) required by the search tool. Launch the Viking Orbiter Product Search to give it a try.
The table below lists the search parameters that can help you narrow down the number of images that are returned by a search of the PDS Viking Orbiter image collection. The images to the right show screen shots of the Viking Orbiter Product Search. Note there are two categories (the tabs above the search form) where these search parameters are found: Quick Search and Geometry.
|
[edit] Browsing by Volume
You can also go to the online data and Browse Online Data Volumes, which offers FTP access to the CDs (compact discs)used to archive and distribute the data. This allows you to look at the image and text files on the CDs, where you can find more helpful information. To give it a try, launch the Planetary Image Atlas in a new browser window. Now click the Viking Orbiter Browse Online Data Volumes and choose a CD volume to look at. When you know the images that you would like to work with, you can go to this area with an FTP tool and download that image or download it using your browser.
[edit] Related Resources
[edit] Data Acquisition Tool: USGS Planetary GIS Web Server
The USGS Planetary GIS Web Server, hosted by the USGS Astrogeology Research Program, allows a user to view Viking footprints and verify image coverage. The site delivers a variety of data sets through a web GIS interface. When searching for imagery, the Planetary GIS site's ability to display footprints of data can prove very helpful in verifying gaps, or determining image placement and overlaps.
As illustrated in the screen shot shown here on the right, using the Mars General ArcIMS HTML Viewer:
- Zoom in to your area of interest
- Select Viking Footprints less than 100 m/p (meters per pixel) in the Layers on the right side of the screen (you can also choose resolution ranges from 100 to 300 m/p and greater than 300 m/p ).
- Select Viking Footprints less than 100 m/p from the Current Active Layer menu above the Layers menu.
- Click the Identify Tool (circle with an 'i' in it) from the Misc toolbox on the left side of the screen.
- Click on a footprint shown on the map. Information about the footprint (or footprints) that covers the point you clicked will appear in the bottom panel of the screen below the map.
[edit] Resources
- Mars Online Maps page on the USGS Planetary GIS Web Server
[edit] Data Acquisition Tool: JMARS
JMARS is a useful Geographic Information System (GIS) tool to evaluate Viking images that cover an area of interest before the images are downloaded. The tool displays Viking footprints and a variety of other Mars data. JMARS can be used to:
- query the database of Viking images,
- select browse images to display on-screen and download via the web,
- generate a list of Viking images (great for creating scripts), and
- save the displayed map as an image.
Give it a Whirl!
If you have JMARS installed, launch it and log in. We'll run through a quick and easy exercise in displaying Viking footprints.
- In the Main tab of the Layer Manger, hit the Add new layer button, which opens a menu.
- Select Viking from the Stamp menu.
- In the Add Viking stamp layer window, just hit the Okay button, leaving all the fields blank.
- A new tab named Viking stamps will appear in the Layer Manager. When it's done loading the footprints, its drawing status indicator will turn from red to green,the footprints will be displayed on the map and the images shown on the map are list in the Layer Manager.
- Try right-clicking on a listing the image list and on the footprints displayed on the screen -- there's lots of options for working with and accessing information and data. For example, Render and Load Selected Stamps will download and display the Viking images for the selected footprints on the map, giving you the ability to preview the data. Web Browse will launch an image's web page in your browser so you can access the information and data.
Of course, there's many other options in JMARS to help you search for Viking data, such as the tools for narrowing your search and modifying your display in the Settings, Query, and Render tabs in the Layer Manager, using the various tools in the main menus, and adding other useful data layers to the display.
[edit] Resources
- Download JMARS (free, registration required to use JMARS' full functionality)
- JMARS User Manual
[edit] Importing Viking Orbiter Data
Viking VIS data are distributed in Standard Data Products formatted files, which have an .imq extension, are compressed PDS format images and are decompressed before ingesting into Isis.
The Viking Orbiter images that are distributed on compact disc (CD) are also compressed image files. The CDs are formatted according to the ISO-9660 standard. Viking CDs can be obtained from the NASA National Space Science Data Center.
[edit] Using vik2isis to ingest VIS images into Isis
The following examples show the use of vik2isis to ingest (or import) a VIS image into Isis. The resulting output file will be an Isis cube.
Example: ingesting a compressed Standard Data Products VIS image
vik2isis FROM=Viking_input.imq To=Viking_image.cub
The decompression software for the .imq images is included within vik2isis. You don't need to worry about the extra step of decompressing the image. Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
- vik2isis: Viking data ingestion
[edit] Viking VIS Problem Data
Many of the problems with the Viking data set are due to environmental conditions that existed when the image was acquired. To find these poor quality images, you must visually inspect the images. Clouds and airborne dust are two elements that will degrade the quality of your images. The amount of image degradation will vary. Whether or not you use the image is a judgment based on how much information will be gained verses how much the image will degrade the final product.
 |  |
[edit] Adding SPICE
An important capability of Isis is the ability to geometrically and photometrically characterize pixels in raw planetary instrument images. Information such as latitude, longitude, phase angle, incidence angle, emission angle, local solar time, sun azimuth, and a many other pixel characteristics can be computed.
To compute this information, the SPICE (Spacecraft and Planetary ephemeredes, Instrument C-matrix and Event kernel) kernels must first be determined for the particular raw instrument image. These kernels maintain the spacecraft position and orientation over time as well as the target position and instrument specific operating modes.
To add SPICE information to your cube, run spiceinit application on the image so that camera/instrument specific applications (e.g., cam2map, campt, qview) will have the information they need to work properly. Generally, you can simply run spiceinit with your input filename and no other parameters:
spiceinit FROM=my.cub
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
- spiceinit: adds SPICE information to the input cube
[edit] Level 1 Processing - Noise Removal and Radiometric Calibration
To create a Level 1 Viking image, we'll clean up noise and other problems and radiometrically correct the data so we have an image representing the reflectance of the surface. We'll start by removing image blemishes caused by malfunctioning detectors, dust specks, transmission noise, and so forth. We'll finish up our Level 1 image with radiometric calibration in order to create an image that is representative of an ideal image acquired by a camera system with perfect radiometric properties.
 |  |  |  |  |
[edit] Overview of Noise And Artifacts
Noise and artifact are terms used to describe speckles, spikes, reseaus, missing data, and other marks, blemishes, defects, and abnormalities in image data created during the acquisition, transmission, and processing of image data. The line between the definitions of artifact and noise is fuzzy (and often subject to opinion), and often the terms are used interchangeably. Some noise and artifacts are expected, even purposefully added, and can be removed during the radiometric calibration process.
[edit] What is noise?
In image processing, noise is a type of flaw or blemish in the image caused by:
- Telemetry data dropouts or transmission errors
- Malfunctioning or dead detectors
- Read noise native to the CCD system
- Coherent noise caused by spurious electronic signals from the operation of instruments onboard the spacecraft
Noise can take the appearance of speckling, missing data, random or orderly patterns, and other variations that cause the image to have a muddled appearance, or visually distracting blemishes or patterns. There are three categories of noise:
- Fixed-location noise always exist at the same location in the image array, with predictable positions. Fixed location noise can be cosmetically corrected by replacing the bad pixels with the weighted average of the unaffected neighborhood pixels. Fixed-location noise can result from malfunctioning or dead detectors.
- Randomly occurring noise results from data transmission errors causing data bits to be altered at random intervals in the image. The random noise produces discrete, isolated pixel variations or "spikes" and gives an image a "salt-and-pepper" appearance. Additionally, telemetry drop-outs can cause portions of an image to be completely missing. This type of noise is generally corrected using filtering techniques that recognize missing or anomalous data pixels and replaces these data points with a weighted average of the unaffected neighborhood pixels.
- Coherent noise can be introduced by spurious electronic signals produced by the operation of instruments onboard the spacecraft during image observations. The spurious signals interfere with the electronics of the imaging system causing coherent noise patterns to be electronically "added" to the images. For example, the shuttering electronics of the Viking cameras introduced a spurious "herring-bone" pattern at the top and bottom of the image. Noise-removal algorithms are designed to correct specific coherent noise problems such as this one.
[edit] What are artifacts?
Generally, image artifacts are a type of flaw or blemish in the image introduced during processing, intentionally introduced due to the design of system, or unintentional introduction of debris or energy external to the system. Examples of artifacts include:
- reseaus etched on the camera lens
- reseaus exposed on photographic film during pre-flight preparations for a mission
- minute dust specks located in the optical path or on the focal plane array
- cosmic rays and other charged particles impacting the sensor (particularly CCDs)
- fringe, ring, or visible patterns created during filtering, ratio analysis, and other enhancement processes
- quantization, checkerboarding, and other artifacts introduced by image compression algorithms during conversion from Isis cube format to a lossy image format or bit-type reductions that reduce the tonal resolution of the data
Most artifacts fit neatly into the categories of noise listed earlier and are corrected using many of the same processes. For example, dust specks create fixed-location blemishes, and cosmic rays cause random spikes. Reseaus are useful blemishes that are removed once they are analyzed for their locations within an image and the information saved for later processing.
 Reseaus, dropped data, and salt-and-pepper This example shows a number of noise and artifact types. The large, regularly spaced black dots across the image are caused by the reseaus on the camera lens. The pattern of vertical black lines across the bottom of the image was caused by transmission data loss. The black and white speckles, called salt-and-pepper, are random noise. |
 Instrument error The black streak running down the right side of this image may have been caused by an unusual error in the line-scanner camera that acquired this image. |
 Transmission error A glitch during the transmission of this image caused the data to become garbled (upper right) and some data was completely lost (the black area across the middle) |
 Image compression Exporting the image to a lossy, compressed image format (using very high compression), the compression algorithm introduced a tiled pattern across the image. |
[edit] Removing Salt Noise
The black and white speckle present in Viking images is a result of interference during the transfer of information from the spacecraft. This speckle is called salt and pepper noise because it has the appearance of grains of salt and pepper sprinkled across the image.
Removing Salt Noise
The application viknosalt runs the application noisefilter five times to identify white noise within the image. The identified pixels are set to a value of null. The final step in viknosalt is a low pass filter that replaces the null pixels with a valid value.
viknosalt FROM=Viking_image.cub TO=Viking_nosalt.cub
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
- viknosalt: Viking salt noise removal application
 |  |  |  |
[edit] Removing Reseaus
Reseau marks on Viking images are small dots that form a grid of points across the image. These marks are created by design -- reseaus are etched in a pattern over the lens of the camera, and the marks the reseaus make on the image will allow us to refine the image in later processing steps. The images below show reseau marks on a Vidicon tube similar to the ones used for the Viking VIS cameras, and an enlargement of a reseaus mark in a Viking image.
The next step is to find and remove reseaus. The reseau locations found in this step are used to correct for the optical distortion. The vidicon cameras used by the Viking spacecraft have electronic distortions similar in pattern to the optical distortion in a film camera. These electronic distortions are introduced because the scanning pattern of the electron beam used to read out the charge-stored image vidicon is more "barrel-shaped" than rectangular. Interactions between the charge on the photo-cathode that represent the image itself and the electron beam produce additional complex high-order distortions.
Reseaus removal is accomplish by using two applications: findrx to find the reseaus, then remrx to remove them. Finding Reseaus with findrx
findrx will read in a cube and refine the position of the reseau points based on information about where the reseaus should be and comparing those areas of the image against a Viking reseau pattern to locate the actual reseau mark in the image. The image labels are then modified to reflect the new sub-pixel accuracy. Findrx will read in a cube and refine the position of the reseau points. The image labels are then modified to reflect the new position of the reseau with sub-pixel accuracy.
Maybe: describe the label change and show that section of labels
findrx Example: The following example shows running findrx on the command line.
findrx FROM=Viking_nosalt.cub
[edit] Removing Reseaus with remrx
remrx removes reseaus from a Viking image. When you select a value for the parameters sdim (sample dimension) and ldim (line dimension), you want to choose values that are large enough to remove the reseaus but, the value should not be larger then required or you will remove valid data. For most Viking images we have found that of sdim= 9 and ldim= 9 works well. While the reseaus are visibly removed from the images, the reseau information is retained in the labels for later processing stages.
remrx Example: The following example shows running findrx on the command line.
remrx FROM=Viking_nosalt.cub TO=Viking_norx.cub sdim=9 ldim=9
 |  |
Comparisons of remrx with different ldim/sdim parameters: The following close-ups show the results of using remrx with slight changes to ldim and sdim parameters.
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
[edit] Removing Pepper Noise
Currently, the Isis 3 application to remove the black speckle called pepper noise is under development. When the application is released, we will develop a page here in this lesson providing you with examples of pepper noise and tips for running viknopepper to remove this type of noise from your Viking images.
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
- viknopepper: Viking pepper noise removal application
[edit] Remove Missing Track Noise
The missing track noise is caused by interference from the spacecraft electronics. Track noise appears as a regular pattern of NULL values across the image in increments of seven pixels. This noise occurs because of the way Viking images were transmitted to Earth. On the spacecraft, an image is broken into seven tracks, each track contains every seventh value along a scan line. If errors occurred while a track was transmitted to Earth, then the track contains incorrect data values. Sometimes, several tracks are missing.
The program vikfixtrx will check for this type of noise in each of the seven tracks of a Viking image cube. If the threshold of invalid pixels in a given track is met or exceeded, then the track is considered bad and all pixels are replaced by interpolating valid values from either side of the bad pixels.
vikfixtrx Example: The following example shows running vikfixtrx on the command line:
vikfixtrx FROM=Viking_norx.cub TO=Viking_notrx.cub
 |  |
vikfixtrx Close-up: The following is a close-up of the null tracks and results of removing the null tracks with vikfixtrx
 Input image |
 Output image (null tracks removed) |
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
- vikfixtrx: Viking track noise removal application
[edit] Overview of Radiometric Calibration
[edit] Why perform radiometric calibration?
Both vidicon cameras (such as those carried on-board the Viking and Voyager missions), and charge coupled device (CCD) cameras (such as on the Clementine, Mars Reconnaissance Orbiter, and other contemporary missions) produce digital images with the inherent artifact known as camera shading. Camera shading results from the non-uniform sensitivity across the field-of-view of the imaging instrument.
Perhaps the best way to illustrate camera shading is to imagine acquiring a digital image of a target of uniform brightness, say a screen that has been painted a uniform shade of gray. If the camera sensitivity across the fields-of-view were ideal (and the flat-field target exactly the same brightness everywhere), then the acquired digital image would have the same DN value for all the pixels in the image. However, because of the non-uniform sensitivity of the camera, the DN values of the resulting image will vary throughout the image array (see the example to the right). A typical camera may have as much as 20% variation across the field-of-view. Camera shading corrections are applied to an image that correct for the non-uniform sensitivity so that, in our flat-field observation example, the radiometrically corrected image would contain pixels of identical value.
[edit] What is radiometric calibration?
Radiometric calibration recalculates the DNs in an image based on numerous factors, such as the exposure time, known values for the camera shading based on flat-field observations, dark current (output current of a detector when no energy is incident on the detector, such as when the shutter is closed), and other factors describing the unique electronics design and characteristics of an imaging system. Camera sensitivity may be time dependent because of the drift of the camera sensitivity throughout the course of the mission. The camera sensitivity is also dependent on the filter, operating modes of the instrument, and temperature of the cameras. Additionally, the camera response may be non-linear at various brightness levels.
[edit] How is the image changed by radiometric calibration?
A radiometrically calibrated image has DNs in radiometric units that are proportional to the brightness of a scene. Radiometric calibration applications in Isis produce output values that represent either:
- Radiance - The amount of electromagnetic energy emitted or reflected from an area of a planet, in units of µw/(cm2*sr)
- Reflectance - The ratio of reflected energy to incoming energy (i.e. irradiance/solar flux, often simply called I/F). A reflectance would be 1.0 for an ideal 100% reflector where the sun and camera orientations are perpendicular to the reflecting surface.
Generally, Isis radiometric calibration applications that offer both reflectance and radiance output will output reflectance by default. Due to the fact that radiometric calibration is mission dependent, each mission supported by Isis has its own radiometric calibration application. A few examples of radiometric calibration applications in Isis are:
[edit] Radiometric Calibration of Viking VIS Data
vikcal performs radiometric corrections to planetary images acquired by the Viking orbiter cameras. vikcal performs a radiometric correction in two steps:
- Correct the varying response of the vidicon across the field of view of the camera. Multiplicative and additive correction coefficients, as a function of line and sample position, are applied to an image array to produce the results of an 'ideal' camera.
- Convert the image data to reflectance values, where reflectance (a value between 0 and 1) is the ratio of the observed radiance and the radiance of a white screen, normal to the incident rays of the Sun.
vikcal Example: The following example shows the command line for running the Viking radiometric calibration application (vikcal):
vikcal FROM=Viking_notrx.cub TO=Viking_cal.cub
The output image of vikcal will be a 32-bit (floating-point) cube, where the pixel values represent reflectance.
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
[edit] Level 2 Processing - Geometry
Producing a mosaic requires geometric processing on the individual images that make up the desired mosaic. The individual images are geometrically transformed from spacecraft camera orientation to a common map coordinate system. Isis has generic software applications that are applied to all supported mission data. Based on the information in the image labels that was added in our earlier steps, the software recognizes the instrument and performs accordingly.
Within Isis, the geometric software includes correcting camera distortions for each supported instrument. The camera distortion correction and geometric transformation are performed simultaneously so that an image is resampled only once and resolution loss is minimal. The transformation is based on the original viewing geometry of the observation, relative position of the target and the definition of the map projection.
[edit] Overview of Map Projecting Images
Converting a raw instrument image to a map projected image is a fundamental capability of Isis. The target definition, ground range, pixel resolution, map projection, and projection dependent parameters are all needed in order to produce a map projected image.
[edit] Projecting the Image
The cam2map application converts a camera (instrument) image to a map projected image. cam2map will automatically compute defaults for most of the mapping parameters, so you only need to define a subset of the parameters in your map template (e.g. ProjectionName).
- Your cube must be data from a Isis-supported mission -- cam2map depends on camera/instrument information in the Isis system to perform map projections.
- If you are projecting several images with the same projection parameters, you can reuse the same map template for all your images simply by removing the latitude longitude range parameters (MinimumLatitude, MaximumLatitude, MinimumLongitude, and MaximumLongitude) from your map template.
- cam2map will automatically calculate parameter values for you -- all you really need is the projection name in your map template.
- If you're planning on mosaicking your projected images, make sure the PixelResolution is the same for all images. Some projections also require the CenterLongitude and CenterLatitude to be the same when creating a mosaic.
[edit] Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
- maptemplate: set up a map projection parameter template for map projecting cubes
- cam2map: project a cube to a map projection
[edit] Level 3 Processing - Photometric Correction
Currently, Isis 3 photometric correction capabilities are under development. When the applications are released, we will develop a page here in this lesson providing you with examples and tips for using Isis photometric correction tools.
Photometric normalization is applied to all images that make up a mosaic in order to adjust and balance the brightness levels among the images that were acquired under the different lighting conditions.
Generally, radiometrically calibrated spacecraft images measure the brightness of a scene under specific angles of illumination, emission, and phase. For a planetary body that doesn't have a significant atmosphere, this brightness is controlled by two basic classes of information: the intrinsic properties of the surface materials, (including composition, grain size, roughness, and porosity), and local topography of the surface.
[edit] Level 4 Processing - Mosaicking
Currently, Isis 3 photometric correction capabilities are under development. When the applications are released, we will finish developing this lesson and provide you with tips for using Isis to create your final, seamless mosaic using mapmos and tone matching procedures and applications.
The final steps in our processing will produce a seamless mosaic of all the images in our region of interest. In spite of best efforts at radiometric calibration and photometric normalization, small residual discrepancies in image brightnesses are likely to remain. These brightness differences appear as seams in a mosaic. There are a couple of methods that will minimize the seams resulting in an improved aesthetic result for a final mosaic. The accuracy and quality of the radiometric calibration and photometric normalization effects how well the seams can be minimized.
[edit] Exporting Isis Data
Naturally, once you're finished processing your image data and you have your final product, you'll want to use it in reports, papers, posters, web pages, your favorite Geographic Information System (GIS) or image analysis package, or simply share it with others. Since many other software packages can't read Isis cube format, you'll want to export your cube to a file type appropriate to your needs.
[edit] General Purpose: Desktop Applications and Web
isis2std (Isis to Standard formats) exports your cubes to a wide variety of popular image formats, such as PNG (Portable Network Graphics) and TIFF (Tagged Image File Format). No matter what desktop application you're using (Word Perfect, Illustrator, or GIMP, just to name a few), or what you're creating (posters, web pages, or a pretty background for your desktop), isis2std will handle it.
[edit] But There's More! GIS and Image Analysis Applications
But the icing on the cake is that isis2std also exports the necessary files for taking your image into GIS! If your cube has Mapping labels, isis2std will write a world file that provides GIS software, and other software which can take advantage of a geographically registered image, with the necessary information to properly display your image. Most applications designed to work with remotely sensed and map data (such as Arc products, Envi, and Global Mapper) can use TIFF, JPEG, and other images with world files. Several geographic software applications even have support for planetary data.
[edit] Astronomy Anyone?
isis2fits (Isis to FITS format) exports your cubes to Flexible Image Transport System (FITS) format, a standard in the astronomical community. There's lots of software designed to work with FITS (even a few common applications and software libraries , like ImageMagick and GIMP). In general, FITS format is useful for mission team members who are working with cruise data to analyze instrument calibration, camera pointing, and other factors. Since cruise image data frequently contain stars, astronomy software comes in quite useful for this type of work.
[edit] Just the Data, Ma'am
isis2raw (Isis to Raw format) exports an individual band in your cube to raw image format, a minimal format that contains just the data in the bit-type of your choosing. isis2raw is a good choice when none of the other formats Isis can export to will work for you. In order to import a raw image into another application, you will need to know the width (samples), height (rows), bit-type, and endianess of your raw file in order to import it correctly, so remember to keep track of the parameters you used to export your cube. Related Isis Applications
See the following Isis documentation for information about the applications you will need to use to perform this procedure:
