The last in this series (parts one, two, three, and four). The previous applications have been primarily focused on remote sensing applications, but there are also a number of general purpose freeware GIS programs that include significant remote sensing analysis capabilities.
A powerful but often difficult to use GIS program. Quantum GIS is implementing an easier interface for GRASS’s capabilities. A Java version of GRASS (JGRASS) is being built on top of uDIG, but is concentrating on hydrogeological and geomorphological capabilities for now.
- Canonical component analysis (CCA)
- Color composite generation
- Edge detection
- Frequency filtering (Fourier, convolution matrices)
- Fourier and inverse fourier transformation
- Histogram stretching
- IHS transformation to RGB
- Image rectification (affine and polynomial transformations on raster and vector targets)
- Ortho photo rectification
- Principal component analysis (PCA)
- Radiometric corrections (Fourier)
- Resampling
- Resolution enhancement (with RGB/IHS)
- RGB to IHS transformation
- Texture oriented classification (sequential maximum a posteriori classification)
- Shape detection
- Supervised classification (training areas, maximum likelihood classification)
- Unsupervised classification (minimum distance clustering, maximum likelihood classification)
gvSIG is moving towards release of version 2.0, which will add a substantial number of remote sensing analysis functions. If you want to look at an early version, there’s a 1.9 alpha release available.
– Clipping of bands and data
– Export layers
– Save from view to raster file
– Color table and gradient edition
– No data values management
– Pixel process (filters)
– Color interpretation management
– Overview creation
– Enhanced radiometric
– Histogram
– Geolocation
– Raster reprojection
– Georeferencing
– Automatic vectorization
– Band algebra
– Region of Interest (ROI) definition
– Supervised classification
– Semi-supervised classification
– Decision tree
– Transformations
– Image fusion
– Mosaic
– Scatter diagram
– Image profiles
Integrated Land and Water Information System, formerly commercial software, now open source.
- Image enhancement (contrast, linear stretching)
- Filtering
- Band combination and compositing
- Band ratios and indices
- Georeferencing
- Multi-band statistics
- Principal component analysis
- Image arithmetic
- Image fusion (e.g. pan-sharpening)
- Image classification
A very strong terrain/DEM analysis program, but has other applications as well, including remote sensing.
- Contrast enhancement
- Filters
- Band histograms
- Correlation (covariance) matrix
- Scattergrams
- Band ratios and normalized indices (e.g. NDVI)
- Principal components analysis
- Multi-band merges
- Image training and classification
- Hyperspectral image analysis (AVIRIS)
- Image averaging
- Pan-sharpening
Not primarily a remote sensing application, but has some modules for grid manipulation, statistics and analysis that could be useful.
LANDSAT, SPOT, ERS-1 and NOAA/AVHRR Data input; Registration and Geometric Correction; Image Mosaic with gray level equalization; Image Enhancement by Histogram Manipulation; Spatial Filtering; IHS and Principal Components Transformations; Arithmetical Operations; Pixel Values Reading; Maximum-likelihood pixel-based classifier; Image Segmentation and Region Classifiers (Supervised and Unsupervised); LANDSAT and SPOT Images Restoration; Morphological Filters for Images; Mixture Models; Markov-based Techniques for Image Post-Classification; Radar Image Processing.
And if you want to create your own remote sensing analysis program, or add capabilities to a GIS, there’s the Orfeo Toolbox (OTB), an open-source library/API for image processing:
- image access: optimized read/write access for most of remote sensing image formats, meta-data access, simple visualization;
- sensor geometry: sensor models, cartographic projections;
- radiometry: atmospheric corrections, vegetation indices;
- filtering: blurring, denoising, enhancement;
- fusion: image pansharpening;
- feature extraction: interest points, alignments, lines;
- image segmentation: region growing, watershed, level sets;
- classification: K-means, SVM, Markov random fields;
- change detection.