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List of Figures

2.1 Cmake user interface
5.1 OTB Image Geometrical Concepts
6.1 Collaboration diagram of the ImageIO classes
6.2 Use cases of ImageIO factories
6.3 Class diagram of ImageIO factories
6.4 Initial SPOT 5 image
6.5 ROI of a SPOT5 image
7.1 DEM To Image generator Example
8.1 BinaryThresholdImageFilter output
8.2 ThresholdImageFilter using the threshold-below mode.
8.3 ThresholdImageFilter using the threshold-above mode
8.4 ThresholdImageFilter using the threshold-outside mode
8.5 Band Math
8.6 Band Math X
8.7 Band Math X
8.8 GradientMagnitudeImageFilter output
8.9 GradientMagnitudeRecursiveGaussianImageFilter output
8.10 Effect of the Derivative filter.
8.11 Output of the RecursiveGaussianImageFilter.
8.12 Output of the LaplacianRecursiveGaussianImageFilter.
8.13 CannyEdgeDetectorImageFilter output
8.14 Touzi Edge Detector Application
8.15 Effect of the MedianImageFilter
8.16 Effect of the Median filter.
8.17 Effect of erosion and dilation in a binary image.
8.18 Effect of erosion and dilation in a grayscale image.
8.19 DiscreteGaussianImageFilter output
8.20 GradientAnisotropicDiffusionImageFilter output
8.21 Mean Shift
8.22 Lee Filter Application
8.23 Frost Filter Application
8.24 MRF restoration
8.25 DanielssonDistanceMapImageFilter output
9.1 Registration Framework Components
9.2 Fixed and Moving images in registration framework
9.3 HelloWorld registration output images
9.4 Pipeline structure of the registration example
9.5 Registration Coordinate Systems
9.6 Multi-Modality Registration Inputs
9.7 Multi-Modality Registration outputs
9.8 Rigid2D Registration input images
9.9 Rigid2D Registration output images
9.10 Rigid2D Registration input images
9.11 Rigid2D Registration output images
9.12 AffineTransform registration
9.13 AffineTransform output images
9.14 Geometrical representation objects in ITK
9.15 Class diagram of the Optimizer hierarchy
10.1 Estimation of the correlation surface.
10.2 Displacement field and resampling from fine registration
10.3 Displacement field and resampling from disparity map estimation
10.4 From stereo pair to elevation
11.1 Image Ortho-registration Procedure
12.1 ARVI Example
12.2 ARVI Example
12.3 AVI Example
13.1 Simple pan-sharpening
13.2 Pan sharpening
13.3 Bayesian Data Fusion Example inputs
13.4 Bayesian Data Fusion results
14.1 Results of applying Haralick contrast
14.2 PanTex Filter
14.3 Right Angle Detection Filter
14.4 Harris Filter Application
14.5 SURF Application
14.6 Alignment Detection Application
14.7 Line Ratio Detector Application
14.8 Line Correlation Detector Application
14.9 Line Correlation Detector Application
14.10 Line Correlation Detector Application
14.11 Edge Density Filter
14.12 Road extraction filter application
14.13 Spectral Angle
14.14 Road extraction filter application
14.15 Road extraction filter application
14.16 Cloud Detection Example
15.1 Morphological pyramid analysis
15.2 Morphological pyramid analysis
15.3 Morphological pyramid analysis
15.4 Morphological pyramid analysis
15.5 Morphological pyramid analysis
15.6 Morphological pyramid analysis
15.7 Morphological pyramid analysis and synthesis
15.8 Morphological pyramid analysis
16.1 ConnectedThreshold segmentation results
16.2 OtsuThresholdImageFilter output
16.3 OtsuThresholdImageFilter output
16.4 NeighborhoodConnectedThreshold segmentation results
16.5 ConfidenceConnected segmentation results
16.6 Watershed Catchment Basins
16.7 Watersheds Hierarchy of Regions
16.8 Watersheds filter composition
16.9 Watershed segmentation output
16.10 Grid position of the embedded level-set surface.
16.11 FastMarchingImageFilter collaboration diagram
16.12 FastMarchingImageFilter intermediate output
16.13 FastMarchingImageFilter segmentations
17.1 LAIFromNDVIImageTransform Filter
18.1 PCA Filter (forward trasnformation)
18.2 PCA Filter (forward trasnformation)
18.3 PCA Filter (forward trasnformation)
18.4 PCA Filter (forward trasnformation)
18.5 Maximum Autocorrelation Factor results
19.1 Output of the KMeans classifier
19.2 Two normal distributions plot
19.3 Kohonen’s Self Organizing Map
19.4 SOM Image Classification
19.5 SOM Image Classification
19.6 Bayesian plug-in classifier for two Gaussian classes
19.7 SEM Classification results
19.8 Output of the ScalarImageMarkovRandomField
19.9 OTB Markov Framework
19.10 MRF restoration
19.11 MRF restoration
19.12 MRF restoration
19.13 MRF restoration
20.1 Image to Label Object Map
20.2 Object based extraction based on
21.1 Spot Images for Change Detection
21.2 Difference Change Detection Results
21.3 Radarsat Images for Change Detection
21.4 Ratio Change Detection Results
21.5 Kullback-Leibler Change Detection Results
21.6 ERS Images for Change Detection
21.7 Correlation Change Detection Results
21.8 Kullback-Leibler profile Change Detection Results
21.9 Multivariate Alteration Detection Results
22.1 Hyperspectral cube
22.2 Linear mixing model
22.3 Decomposition of the LMM
22.4 Hyperspectral cube vectorization
22.5 Simplex
22.6 Unmixing Filter
22.7 Concept of detection
22.8 Anomaly detection block diagram
22.9 Sliding window and parameters definitions
23.1 Scaling images
23.2 Scaling images
23.3 Scaling images
23.4 Grayscale to color
23.5 Hill shading
24.1 Open street map
25.1 ITK image iteration
25.2 Copying an image subregion using ImageRegionIterator
25.3 Using the ImageRegionIteratorWithIndex
25.4 Neighborhood iterator
25.5 Some possible neighborhood iterator shapes
25.6 Sobel edge detection results
25.7 Gaussian blurring by convolution filtering
25.8 Finding local minima
25.9 Binary image morphology
26.1 ImageAdaptor concept
26.2 Image Adaptor for performing computations
28.1 The Data Pipeline
28.2 Sequence of the Data Pipeline updating mechanism
28.3 Composite Filter Concept
28.4 Composite Filter Example

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