Image Processing in IDRISI Selva

IDRISI includes the largest suite of tools in the industry for the processing of remotely sensed imagery. These tools are integrated within IDRISI and accompany IDRISI’s raster GIS tools, saving effort, costs and resources. With the image processing tools in IDRISI, you can perform image restoration and enhancement, image transformation, image segmentation, image classification including hard and soft classifiers, accuracy assessment, and much, much more.

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.

Image Processing tools in IDRISI include:

Image Restoration

A complete set of geometric and radiometric tools for correcting image registration and removing image distortion.

  • Atmospheric correction using either the Dark Object Subtraction model, Chavez's Cos(t) model, the full radiative transfer equation model, or the Apparent Reflectance Model (ARM).
  • Image mosaicking for color balancing multiple scenes into a single image.
  • Radiance calibration to convert raw DN.
  • Principal components analysis including standardized and unstandardized modes.
  • An interactive image resampling facility.

Image Enhancement

Tools for display image enhancement that highlights information within the image.

  • Image filtering that includes 10 pre-defined filters and the ability to employ a variable sized user-defined filter.
  • Panchromatic merge for image pansharpening of high resolution satellite imagery.

Image Transformation

An extensive base-image transformation tool set.

  • Principal components analysis, including standardized and unstandardized, cross-product and normalized cross-product modes.
  • Canonical correlation analysis for between image series pattern analysis.
  • Minimum noise fraction for variable image noise reduction
  • Vegetation index analysis with 19 slope-based and distance-based indices

Image Classification

The most extensive set of image classifiers in the industry, including hard and soft classifiers.

Image Segmentation

Tools for image segmentation and object-oriented classification.

  • A segmentation tool that produces segments based on spectral similarity.
  • An interactive signature development tool to facilitate signatures from segments.
  • A majority-rule classifier specifically built for segmentation classification.

Other Key Image Processing Features in IDRISI

  • Hyperspectral image analysis and classification
  • Classification accuracy assessment
  • 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
  • A seamless link to IDRISI GIS analysis tools
  • Comprehensive tutorials with data
  • 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

Segmentation Analysis with IDRISI Taiga

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.

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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.      

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