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List of Figures
2.1
Cmake user interface
6.1
OTB Image Geometrical Concepts
7.1
Collaboration
diagram of the ImageIO classes
7.2
Use cases of ImageIO factories
7.3
Class diagram
of ImageIO factories
7.4
Initial SPOT 5 image
7.5
ROI of a SPOT5 image
8.1
DEM To
Image generator Example
9.1
BinaryThresholdImageFilter output
9.2
ThresholdImageFilter
using the threshold-below mode.
9.3
ThresholdImageFilter using the threshold-above
mode
9.4
ThresholdImageFilter using the threshold-outside mode
9.5
Band Math
9.6
Band Math X
9.7
Band
Math X
9.8
GradientMagnitudeImageFilter output
9.9
GradientMagnitudeRecursiveGaussianImageFilter
output
9.10
Effect of the Derivative filter.
9.11
Output of the RecursiveGaussianImageFilter.
9.12
Output
of the LaplacianRecursiveGaussianImageFilter.
9.13
CannyEdgeDetectorImageFilter output
9.14
Touzi
Edge Detector Application
9.15
Effect of the MedianImageFilter
9.16
Effect of the Median
filter.
9.17
Effect of erosion and dilation in a binary image.
9.18
Effect of erosion and dilation in a
grayscale image.
9.19
DiscreteGaussianImageFilter output
9.20
GradientAnisotropicDiffusionImageFilter
output
9.21
Mean Shift
9.22
Lee Filter Application
9.23
Frost Filter Application
9.24
MRF
restauration
9.25
DanielssonDistanceMapImageFilter output
10.1
Registration Framework
Components
10.2
Fixed and Moving images in registration framework
10.3
HelloWorld registration
output images
10.4
Pipeline structure of the registration example
10.5
Registration Coordinate
Systems
10.6
Multi-Modality Registration Inputs
10.7
Multi-Modality Registration outputs
10.8
Rigid2D
Registration input images
10.9
Rigid2D Registration output images
10.10
Rigid2D Registration input
images
10.11
Rigid2D Registration output images
10.12
AffineTransform registration
10.13
AffineTransform
output images
10.14
Geometrical representation objects in ITK
10.15
Class diagram of the Optimizer
hierarchy
11.1
Estimation of the correlation surface.
11.2
Displacement field and resampling from
fine registration
11.3
Displacement field and resampling from disparity map estimation
11.4
From
stereo pair to elevation
12.1
Image Ortho-registration Procedure
13.1
ARVI Example
13.2
ARVI
Example
13.3
AVI Example
14.1
Simple pan-sharpening
14.2
Pan sharpening
14.3
Bayesian
Data Fusion Example inputs
14.4
Bayesian Data Fusion results
15.1
Results of applying
Haralick contrast
15.2
PanTex Filter
15.3
Right Angle Detection Filter
15.4
Harris Filter
Application
15.5
SURF Application
15.6
Alignment Detection Application
15.7
Line Ratio
Detector Application
15.8
Line Correlation Detector Application
15.9
Line Correlation Detector
Application
15.10
Line Correlation Detector Application
15.11
Edge Density Filter
15.12
Road extraction
filter application
15.13
Spectral Angle
15.14
Road extraction filter application
15.15
Road extraction filter
application
15.16
Cloud Detection Example
16.1
Morphological pyramid analysis
16.2
Morphological
pyramid analysis
16.3
Morphological pyramid analysis
16.4
Morphological pyramid
analysis
16.5
Morphological pyramid analysis
16.6
Morphological pyramid analysis
16.7
Morphological
pyramid analysis and synthesis
16.8
Morphological pyramid analysis
17.1
ConnectedThreshold
segmentation results
17.2
OtsuThresholdImageFilter output
17.3
OtsuThresholdImageFilter
output
17.4
NeighborhoodConnectedThreshold segmentation results
17.5
ConfidenceConnected segmentation
results
17.6
Watershed Catchment Basins
17.7
Watersheds Hierarchy of Regions
17.8
Watersheds
filter composition
17.9
Watershed segmentation output
17.10
Grid position of the embedded level-set
surface.
17.11
FastMarchingImageFilter collaboration diagram
17.12
FastMarchingImageFilter
intermediate output
17.13
FastMarchingImageFilter segmentations
18.1
LAIFromNDVIImageTransform
Filter
19.1
PCA Filter (forward trasnformation)
19.2
PCA Filter (forward trasnformation)
19.3
PCA
Filter (forward trasnformation)
19.4
PCA Filter (forward trasnformation)
19.5
Maximum Autocorrelation
Factor results
20.1
Output of the KMeans classifier
20.2
Two normal distributions plot
20.3
Kohonen’s
Self Organizing Map
20.4
SOM Image Classification
20.5
SOM Image Classification
20.6
Bayesian
plug-in classifier for two Gaussian classes
20.7
SEM Classification results
20.8
Output of the
ScalarImageMarkovRandomField
20.9
OTB Markov Framework
20.10
MRF restauration
20.11
MRF
restauration
20.12
MRF restauration
20.13
MRF restauration
21.1
Image to Label Object
Map
21.2
Object based extraction based on
22.1
Spot Images for Change Detection
22.2
Difference
Change Detection Results
22.3
Radarsat Images for Change Detection
22.4
Ratio Change
Detection Results
22.5
Kullback-Leibler Change Detection Results
22.6
ERS Images for Change
Detection
22.7
Correlation Change Detection Results
22.8
Kullback-Leibler profile Change Detection
Results
22.9
Multivariate Alteration Detection Results
23.1
Hyperspectral cube
23.2
Linear mixing
model
23.3
Decomposition of the LMM
23.4
Hyperspectral cube vectorization
23.5
Simplex
23.6
Unmixing
Filter
23.7
Concept of detection
23.8
Anomaly detection block diagram
23.9
Sliding window and parameters
definitions
24.1
Scaling images
24.2
Scaling images
24.3
Scaling images
24.4
Grayscale to color
24.5
Hill
shading
25.1
Open street map
26.1
ITK image iteration
26.2
Copying an image subregion using
ImageRegionIterator
26.3
Using the ImageRegionIteratorWithIndex
26.4
Neighborhood iterator
26.5
Some
possible neighborhood iterator shapes
26.6
Sobel edge detection results
26.7
Gaussian blurring by
convolution filtering
26.8
Finding local minima
26.9
Binary image morphology
27.1
ImageAdaptor
concept
27.2
Image Adaptor for performing computations
29.1
The Data Pipeline
29.2
Sequence of
the Data Pipeline updating mechanism
29.3
Composite Filter Concept
29.4
Composite Filter Example
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