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Image Processing in IDRISI Selva

IDRISI features the largest suite of tools for the processing of remotely sensed imagery that includes supervised and unsupervised classification techniques, based on scientifically proven algorithms and methods, for both multispectral and hyperspectral imagery. Included are industry standard processing and classification tools, and also extensive machine learning classifiers including neural network classifiers.

What makes the software critical for today’s analysts is that image processing data can be completely integrated with IDRISI's equally extensive set of raster GIS tools, saving effort, costs and resources. For over 25 years, Clark Labs has been involved in the development of geospatial technologies, supplying the community with the most comprehensive GIS and image processing system on the market.

Distinctive Image Classification Features

The most extensive set of image classifiers in the industry
A seamless link to IDRISI GIS analysis tools
Comprehensive tutorials to bring you quickly up to speed
Object-oriented image segmentation and classification
Neural network classifiers including Multi-layer Perceptron, Self-organizing Map, Radial Basis Function, and Fuzzy ARTMAP
Machine learning classifiers including classification tree analysis
Land Change Modeler, an application for the monitoring and prediction of land cover change
Earth Trends Modeler, an application for the analysis of image time series
Import support for all the popular data archive formats

Learn More about IDRISI Selva

IDRISI Selva Brochure
IDRISI Selva Technical Specifications
REDD Analysis
Forest Mapping
Land Cover Mapping
Segment-Based Classification

The SEGMENTATION module creates an image of segments that have spectral similarity across many input bands. The image on the left uses a larger similarity threshold than the one on the right, resulting in more generalized, less homogeneous segments. Using this threshold, the image allows for segments that wholly contain building objects.

Neural Network Classification Analysis with IDRISI Taiga

A variety of machine learning classifiers are available within IDRISI. Neural network classifiers include a multi-layer perceptron, self-organizing map, and fuzzy ARTMAP. Each allows complete control over all parameters.