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Sub pixelclassification

Sub pixelclassification. Contact: mirza.waqar@seecs.edu.pk. Mirza Muhammad Waqar. Lecture Overview. Image classification Sub Pixel Classification Sub Pixel Classification – Principal Components of IMAGINE Subpixel Classifier Preprocessing Environmental Correction

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Sub pixelclassification

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  1. Sub pixelclassification Contact: mirza.waqar@seecs.edu.pk Mirza Muhammad Waqar

  2. Lecture Overview • Image classification • Sub Pixel Classification • Sub Pixel Classification – Principal • Components of IMAGINE Subpixel Classifier • Preprocessing • Environmental Correction • Signature Refinement • Material of Interest (MOI) Classification • Unique Features • Benifits

  3. Image Classification • The key objective of classification is to • Allocate each pixel of a remote sensing image into only one class (Hard or Per-Pixel Classification) or • To associate the pixel with many class (i.e. soft, sub-pixel classification)

  4. Sub Pixel Classification • Subpixel Classifier is an advanced image exploitation tool designed to detect materials that are smaller than an image pixel, using multispectral imagery. • It addresses the “mixed pixel problem” by successfully identifying a specific material when materials other than the one you are looking for are combined in a pixel.

  5. Sub Pixel Classification • It is a powerful low cost alternative to • Ground surveys • Field sampling • High-resolution • It discriminates between spectrally similar materials, such as • Individual plant species • Specific water types • Distinctive man-made materials.

  6. Sub Pixel Classification • It allows you to develop spectral signatures that are scene-to-scene transferable.

  7. Subpixel Classification – Principal

  8. IMAGINE Subpixel Classifier • IMAGINE Subpixel Classifier is part of ERDAS IMAGINE Professional software. • It can be used with imagery from any 8-bit or 16-bit airborne or satellite multispectral imaging platform. • Currently, the most common sensor used is the Landsat Thematic Mapper (TM). • SPOT Multispectral (XS), DigitalGlobeQuickBird, and Space Imaging’s IKONOS imagery are also widely used data sources. • The software can also be used with hyperspectral imagery.

  9. Components of IMAGINE Subpixel Classifier IMAGINE Subpixel Classifier Preprocessing Environmental Correction Signature Derivation Signature Refinement Material of Interest (MOI) Classification Two Data Quality Assurance Utilities

  10. Preprocessing • Preprocessing is an automated process that must be performed prior to developing a signature or performing MOI Classification. • There are no interactive results to view, but a preprocessing output file is created. This file is used by other IMAGINE Subpixel Classifier processes. • Preprocessing need only be performed once per image. You can use the same output each time you perform classification or signature derivation.

  11. Environmental Correction • Environmental Correction compensates for unwanted spectral variations in scene pixels. • These variations are caused by differences in atmospheric and other environmental conditions. • One of the benefits of this correction is that signatures derived from corrected images are scene-independent.

  12. Signature Derivation • Manual Signature Derivation is used to generate a single signature from a fixed set of input parameters. • Use Manual Signature Derivation when you want to generate a signature from a whole-pixel training set. • To derive an IMAGINE Subpixel Classifier signature, you must identify pixels which likely contain the material of interest.

  13. Signature Refinement • Signature refinement tool is used to refine extracted signatures.

  14. Material of Interest (MOI) Classification • Classification is the process of finding those pixels • within the scene which have spectral properties that are similar to a given signature material of interest. • IMAGINE Subpixel Classifier can identify materials of interest even when they are • mixed with other materials and occupy only a fraction of the pixel ground sample area.

  15. Unique Features • Multispectral detection of subpixel MOIs • The detection and classification of materials that occupy as little as 20% of a pixel • Detection based on spectral properties, not spatial properties • Scene-to-scene signature transfer

  16. Benefits • Classifies objects that are smaller than the spatial resolution of the sensor • Identifies specific materials in mixed pixels • Creates purer spectral signatures • Can be used for many types of applications • Develops scene-to-scene transferable spectral signatures, even at different times of the day and year • Enables searches over wide geographic areas

  17. Cont… • IMAGINE Subpixel Classifier will enable you to improve the accuracy of your classification projects by making more complete detections. • It offers you higher levels of spectral discrimination and classification accuracy by detecting MOIs even when other materials are present in the pixel.

  18. Cont… • By applying an entirely different approach to background removal and signature development than used by traditional whole pixel classifiers.

  19. Questions & Discussion

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