ERDAS IMAGINE - 2018 Product Release Details
ERDAS IMAGINE® performs advanced remote sensing analysis and spatial modeling to create new information. With ERDAS IMAGINE, you can visualize your results in 2D, 3D, movies, and on cartographic-quality map compositions. Optional modules (add-ons) provide specialized functionalities to enhance your productivity and expand capabilities.
Take advantage of ALL your hardware
ERDAS IMAGINE interface now runs natively in 64-bit, enabling embedded components such as the 2D View and Spatial Model Editor to leverage more of your available system memory and CPUs. Along with streamlined algorithms, this also provides more efficient execution of ERDAS IMAGINE in general.
New operators enable machine-learning classification
Classification algorithms based on machine learning have been implemented as operators in Spatial Modeler. These new operators can be used to perform multi-class prediction.
Use your own algorithms to detect the changes you want to see
Zonal Change detection architecture has been modified to accept custom change detection algorithms. You can now use your own algorithms that better detect changes that are of interest to you. Several optional algorithms are available to choose from as well.
Sensor Independent Complex Data (SICD) support to better read SAR imagery
Modern SAR imagery is often distributed in NITF format with SICD geometry information. Now ERDAS IMAGINE can directly read SICD imagery as well as provide processing options such as orthocorrection.
Exploit multi-segment NITF to better understand your imagery
Modern NITF data can consist of multiple image segments, such as pixel quality information, cloud cover, and multiple tiles of a single image. You can now access and exploit this data much more easily.
New state-of-the-art Pan sharpening operator for exploiting multispectral data
Nearest Neighbor Diffuse (NNDiffuse) algorithm is a state-of-the-art pan sharpening technique to fuse images, originally developed by Rochester Institute of Technology Digital Imaging and Remote Sensing Laboratory. Now the algorithm is available as an operator for use in building Spatial Models capable of deriving information from high resolution multispectral data.
Leverage investments in other Hexagon Geospatial products in Spatial Model Editor
ArcPy (Python site package) scripts are now recognized and you can add them as spatial operators in the Spatial Model Editor operators list. Then you can use them in combinations with other operators to leverage the strengths of both ERDAS IMAGINE and GeoMedia in a Spatial Model.
Build feature extraction workflows and custom classifiers with new operators
Hexagon Geospatial is porting IMAGINE Objective functionality into our powerful Spatial Modeler. Several IMAGINE Objective functionalities (such as classifiers, raster cues, vector cues, vector cleanup operators) are now available as operators and you can use them to build feature extraction workflows. Using the extensibility of Spatial Modeler, you can also create and use your own classifiers or cues to fit your specific application.
New atmospheric correction operator enables easier change detection, feature extraction
Building on the algorithms implemented in the Rapid Atmospheric Correction spatial operator, we added a new spatial operator named Generic Atmospheric that enables any 16-bit imagery with at least four bands in the wavelength range from Coastal Blue to NIR2 to be atmospherically corrected to ground reflectance based on parameters that can be derived from the image header. Correcting to ground reflectance has the advantage of normalizing scene-to-scene variations, which in turn makes tasks such as change detection, standardized classification, and other feature extraction tasks more straightforward.
New operator facilitates spatial models with algorithms using metadata-derived inputs
Read Sensor Metadata operator parses ancillary metadata files provided with imagery to create a dictionary of information about the image. By having this information available, it is much easier to construct Spatial Models that apply algorithms, such as atmospheric correction, whose inputs are automatically derived from available metadata.
Modern higher-resolution imagery supported in 2D View's Scale menu
To support modern higher resolution imagery, additional “zoom to” scale options have been added to the 2D View’s Scale menu.
Easier to open NITF files with multiple segments
NITF files containing multiple segments (including vector overlays) can now be accessed in one step using the NITF Segments file type. Using this option to open a NITF file loads all displayable segments into a single 2D View as individual layers.
Colors can indicate security for classified environments
To support use of the software in classified environments, different colors can be displayed in the title bar of the 2D View based on the security classification of the imagery being displayed.
Sentinel-2 format update solves long pathnames issue
ERDAS IMAGINE can now directly read the updated format for Sentinel-2 satellite data introduced by ESA in late 2016 for Level 1C data to alleviate problems with using long pathnames on Windows computers.
Sentinel-2 “True Color” band combination option lets you choose your blue band
Previously, when using Sentinel-2 13-band data and choosing the True Color band combination (under Multispectral tab), the software used bands 4,3,1 for RGB. The problem is that band 1 of Sentinel-2 data has a lower resolution (60m compared to 10m of bands 4,3,2) and consequently some prefer to use band 2 for Blue, rather than band 1. An option has been added to support this.
Planet imagery format update is now enabled
ERDAS IMAGINE can directly read data in the revised formatting from Planet for RapidEye and PlanetScope imagery, implemented in late 2016.
More band options for Landsat 8 and WorldView-3 make band selection more intuitive
Additional false-color display band combination options have been added for Landsat 8 and WorldView-3 imagery. Such predefined combinations make band selection much more intuitive to the user, especially when considering imagery with many bands.
WorldView-4 support enables direct reading and orthorectification
ERDAS IMAGINE can directly read WorldView-4 imagery from DigitalGlobe, including the ability to orthorectify the imagery.
Easier to set up batch processing for Spatial Modeler
In the Batch dialog, an option has been added to send the subset command to the Batch Editor in a similar form to the way it was populated in ERDAS IMAGINE 2016 and prior. This alleviates the complication of exposing more variables than the user generally wanted to set to perform the batch process that had been created by using the newer Spatial Modeler.
More intuitive variable use in Edit Image Metadata (Image Command Tool) for batch processing
A long-standing dissatisfaction with using the Edit Image Metadata tool to set up a batch job to set the Projection information on a set of imagery (such as TIFF files that only had World File information) was that it was too easy to override the geographic extents of all the images and set them to exactly the same values. This would happen because when Map Info Options dialog was used to set the desired Projection, the dialog also passed in the Map Extent of the first image. Unless you noticed this (and manually set up variables), that single map extent would then be applied by the Batch process to all the input images, along with the desired Projection. In ERDAS IMAGINE 2018, Edit Image Metadata tool has been enhanced so that the Upper Left X, Upper Left Y, Pixel Size X and Pixel Size Y parameters are passed to Batch as variables that pull their information from each input image being processed. Only Projection and Units are passed as fixed values.
New IMAGINE SAR Feature User Guide details radar workflows
In the new IMAGINE SAR Feature User Guide, users can learn how to produce a radar image or image-maps product for (near) real-time noise suppression (Despeckle), Image Annealing, Target Detection, Change Detection, and template-based Feature Extraction
Spatial models can be used as operators for easy reuse in other models
Spatial Models can now be treated as operators in their own right and added to the Operators panel for easy reuse in other models.
Set Band Names operator enables band naming for easier distinction
To assist a user in understanding the information that is being presented in particular bands of an image, the Set Band Names operator enables the layer-specific naming of each band to be set prior to writing out a raster file from a Spatial Model.
Support of PostGIS database and feature data in CSV format
PostGIS database support has been added. Feature data can now be read and stored as CSV (comma-separated values) format files.
New feature-based operators enable feature editing and querying
Rename and remove attributes, change primary geometry, and query feature information using new feature-based operators.
Upgraded geodatabase support to ArcGIS 10.5
ERDAS IMAGINE has upgraded geodatabase support to ArcGIS 10.5.
Updated to the latest EPSG projection dataset
All modules of ERDAS IMAGINE have been updated to include the latest EPSG projection dataset.
Live-link with Google Earth Pro
With the release of Google Earth Pro v7.3x, Google addressed a bug in their COM server that prevented ERDAS IMAGINE's live-link feature from working correctly with it. When Google Earth Pro v7.3x is installed, ERDAS IMAGINE 2018 displays the Google Earth tab, starts Google Earth Pro and enables connectivity to it.
IMAGINE Photogrammetry is a seamlessly integrated collection of software tools that enables you to transform raw imagery into the reliable data layers that are required for all digital mapping, raster processing, GIS raster analysis, and 3D visualization needs. Tight integration with ERDAS IMAGINE means that this is the ideal photogrammetric package for projects involving diverse types of airborne and satellite data.
Additional new sensor support
ERDAS IMAGINE can read the following platforms, and many can also be orthorectified using RPC and other sensor models.