You will find here a short description of the main characteristics of the Orfeo ToolBox software, as well as a list of available functions and algorithms.
Main characteristics
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The power of many – We always look for competitive third parties before writing code. Orfeo ToolBox is built on top of ITK, a popular C++ library for the processing of medical images, and relies on many open source software to implement its functions : GDAL for reading/writing raster/vector data and sensor modeling, OpenCV for machine learning… |
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Built for all – Orfeo ToolBox source code is written in a portable way so that OTB supports all major operating systems. Binary packages are provided for many of them. Have a look to the Download page. |
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Scalable – Orfeo ToolBox has been originally developed for Very High Resolution imagery (VHR), and as such is able to scale up to the size of those images. Most of the algorithms implemented in OTB supports piece-wise processing, allowing to process very large image under memory constraints. Most of them are also seamlessly multi-threaded. |
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Flexible – Orfeo ToolBox C++ API is a collection of algorithmic components that spawn almost unlimited combination for processing chains. Even when using the applications which are tools providing processing chains for standard remote sensing tasks without writing one line of code, flexibility is not far. Found that the application is not exactly what you need ? Fork it and write your own application! |
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State of the art – We try our best to keep Orfeo ToolBox with the state of the art of remote sensing image processing, while increasing the number of functions available. OTB can perform in many domain : geometric and radiometric preprocessing,image classification, fusion, change detection, object based image analysis, feature extraction… |
Functions and algorithms
Supported formats
- Image formats supported by GDAL (tiff, hrd, img, data providers specifics …)
- Vector formats supported by GDAL/OGR (shapefile, sqlite, postgis …)
- Digital Elevation Models supported by GDAL
- KMZ image export
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Image manipulation
- Formats and encoding conversion
- Bands or Region of Interest extraction, bands stacking or splitting, image mosaicking
- Linear and non-linear filtering
- Morphological pyramid and morphological profiles
- Fourier and Wavelets transforms
- Generic band calculus
- Color-mapping
- Block-matching
- Point sets density estimation filters
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Data pre-processing
- Radiometric calibration and atmospheric corrections (TOA, TOC)
- Geometric modeling
- Accuracy refinement based on ground control points
- Registration (sensor to sensor)
- Ortho-rectification (sensor to ground)
- Pan-sharpening
- Stereo-rectification (pseudo-epipolar resampling)
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Features extraction
- SIFT and SURF keypoints detection
- Keypoints matching
- Line Segment Detector
- Radiometric indices
- Spectral angle
- Local statistics
- Local Geometric Hu and Flusser moments
- Haralick, PanTex and Structural Feature Set texture features
- Local Histogram of Oriented Gradients
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Image Segmentation
- Conversion between labeled raster and GIS vector file
- Watershed, connected-components, MeanShift with raster or vector results
- Large Scale MeanShift framework for segmentation of very large images
- Object Based Image Analysis with attributes computation and filtering
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Image Classification
- Supervised image classifier training with 9 different machine learning algorithms, including SVM and Random Forest
- Multi-threaded image classification filter
- Various unsupervised (clustering) algorithms such as K-Means or Self Organizing Maps
- Confusion matrix computation with respect to reference or ground truth data
- Classification map regularization
- Fusion of several classification maps
- Object Based Image Classification
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Change detection
- Local metric based change detection framework
- Multi-variate Alteration Detector
- Change-detection by supervised classification
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Hyperspectral processing
- Dimensionality reduction with PCA, NAPCA, ICA, MAF
- Dimensionality estimation with Virtual Dimensionality and ELM
- VCA endmembers extraction
- Unmixing with ISRAU, MDMD-NMF, NCLSU, sparsity based algorithms
- Local RX anomaly detector
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SAR processing
- SAR image manipulation (amplitude and phase image filters)
- TerraSAR-X radiometric calibration
- Speckle reduction filters (Frost, Lee)
- SAR specific features extraction algorithm (Touzi detector, line Correlation and line ratio detector)
- Polarimetric analysis and synthesis filters
- Interferometry
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