ERDAS_IMAGINE_2018_Release_Guide_erdasimagine

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RELEASE GUIDE

ERDAS IMAGINE

February 27, 2018

 
 
February 27, 2018  2 
Contents 
About This Release .................................................................................................................. 8 
ERDAS IMAGINE Product Tiers .............................................................................................. 8 
New Platforms .......................................................................................................................... 8 
64-Bit .................................................................................................................................... 8 
ERDAS IMAGINE 2018 (64-bit) ...................................................................................... 9 
ERDAS IMAGINE 2018 (32-bit) ...................................................................................... 9 
Support of New Feature / Vector Data Formats .................................................................. 10 
ArcGIS 10.5.1 ..................................................................................................................... 10 
ERDAS Foundation Deprecated ......................................................................................... 10 
New Licensing .................................................................................................................... 11 
New Technology ..................................................................................................................... 12 
Machine Learning Classification Operators ........................................................................ 12 
NNDiffuse Pan Sharpening Operator .................................................................................. 12 
Feature Extraction Operators ............................................................................................. 13 
Other New Operators for Spatial Modeler ........................................................................... 13 
Analyze Radiance ......................................................................................................... 13 
Classify Using K-Means ................................................................................................ 14 
Classify Using Deep Learning ....................................................................................... 15 
Classify Using Machine Learning .................................................................................. 15 
Compute Axis Length .................................................................................................... 15 
Compute Circularity ...................................................................................................... 16 
Compute Compactness ................................................................................................. 16 
Compute Concavity ....................................................................................................... 17 
Compute Convexity ....................................................................................................... 17 
Compute Corner Count ................................................................................................. 17 
Compute Eccentricity .................................................................................................... 18 

 
February 27, 2018  3 
Compute Horizontal Skewness ..................................................................................... 18 
Compute Orientation ..................................................................................................... 18 
Compute Orthogonality ................................................................................................. 19 
Compute Primary Axis Skewness ................................................................................. 19 
Compute Rectangularity ................................................................................................ 19 
Compute Secondary Axis Skewness ............................................................................ 19 
Compute Vertical Skewness ......................................................................................... 20 
Convert ......................................................................................................................... 20 
Convert To Surface ....................................................................................................... 20 
Create Bounding Box .................................................................................................... 21 
Create Centerline .......................................................................................................... 21 
Create Centerpoint ........................................................................................................ 21 
Create Centroid ............................................................................................................. 22 
Create ConvexHull ........................................................................................................ 22 
Create File Dataset Reference ...................................................................................... 22 
Create Fitted Bounding Box .......................................................................................... 23 
Create Oriented Bounding Box ..................................................................................... 24 
Create Skeleton ............................................................................................................ 25 
Data Information ........................................................................................................... 25 
Define Deep Learning 2D Convolution Layer ................................................................ 25 
Define Deep Learning 2D pooling Layer ....................................................................... 26 
Define Deep Learning Activation Layer ......................................................................... 26 
Define Deep Learning Dense Layer .............................................................................. 26 
Define Deep Learning Flatten Layer ............................................................................. 27 
Define Functional Attributes .......................................................................................... 27 
Define Processing Area ................................................................................................ 27 
Eliminate Unwanted Areas ............................................................................................ 28 

 
 
February 27, 2018  4 
Extract NITF Shapefile .................................................................................................. 28 
Find Item ....................................................................................................................... 29 
Generic Atmospheric Correction ................................................................................... 29 
Get AWS Landsat 8 Scenes ......................................................................................... 30 
Get Band IDs ................................................................................................................ 31 
Get DRA Params .......................................................................................................... 32 
Get ECW Options ......................................................................................................... 32 
Get JFIF Options ........................................................................................................... 33 
Get JPEG 2000 Options ................................................................................................ 34 
Get Multispectral DRA Params ..................................................................................... 34 
Get NITF 2.x Options .................................................................................................... 35 
Get Preference Value ................................................................................................... 35 
Get Raster Values By Percentage ................................................................................ 35 
Get Referenced Dataset ............................................................................................... 37 
Get SIPS Defaults ......................................................................................................... 37 
Generate Functional Attributes ..................................................................................... 38 
Initialize CART .............................................................................................................. 38 
Initialize Deep Intellect .................................................................................................. 38 
Initialize Inception ......................................................................................................... 39 
initialize K-Nearest Neighbors ....................................................................................... 39 
Initialize Naive Bayes .................................................................................................... 39 
Initialize Random Forest ............................................................................................... 39 
Initialize SVM ................................................................................................................ 40 
Intersect Features ......................................................................................................... 40 
Kurtosis Texture Per Feature ........................................................................................ 40 
Machine Intellect Information ........................................................................................ 41 
Machine Intellect Input .................................................................................................. 41 

 
February 27, 2018  5 
Machine Intellect Output ............................................................................................... 42 
Mask features ............................................................................................................... 42 
Merge Features ............................................................................................................. 42 
Mean Euclidian Distance Texture Per Feature .............................................................. 42 
Metadata Input .............................................................................................................. 43 
Normalize Height .......................................................................................................... 43 
Orthogonalize Geometry ............................................................................................... 44 
Pan Sharpen By NNDiffuse ........................................................................................... 44 
Range Stretch ............................................................................................................... 44 
Raster Cache ................................................................................................................ 44 
Raster Statistics Per Feature ........................................................................................ 45 
Read Sensor Metadata ................................................................................................. 45 
Remove Attributes ........................................................................................................ 46 
Rename Attributes ........................................................................................................ 46 
Select Attributes ............................................................................................................ 47 
Set Band Names ........................................................................................................... 47 
Set Primary Geometry................................................................................................... 48 
Simplify Geometry ......................................................................................................... 48 
Skew Texture Per Feature ............................................................................................ 49 
Split By Skeleton ........................................................................................................... 50 
Stack Count .................................................................................................................. 50 
Tasseled Cap ................................................................................................................ 51 
Update Statistics ........................................................................................................... 51 
Variance Texture Per Feature ....................................................................................... 51 
General Spatial Modeler ..................................................................................................... 52 
Acceptable Values and other Input Contraints .............................................................. 52 
Stack <Statistics> Operators ......................................................................................... 53 