Have a question? Try asking one of our Experts
Two major categories of image classification techniques include unsupervised (calculated by software) and supervised (human-guided) classification.
Unsupervised classification is where the outcomes (groupings of pixels with common characteristics) are based on the software analysis of an image without the user providing sample classes. The computer uses techniques to determine which pixels are related and what classes belong together. The user can specify how many times the data are analyzed and the desired number of output classes but otherwise does not intervene in the classification process. However, the user must have knowledge of the area being classified when the groupings of pixels with common characteristics produced by the computer have to be related to actual features on the ground (such as wetlands, developed areas, coniferous forests, etc.).
Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these choices as references for the classification of all other pixels in the image. Training areas (also known as testing sets or input classes) are selected based on the knowledge of the user. The user also sets the bounds for how close the matches have to be. These bounds are often set based on the spectral characteristics of the training area, plus or minus a certain increment (often based on "brightness" or strength of reflection in specific spectral bands). The user also designates the outputs (for example, how many final classes are needed).
Many analysts use a combination of supervised and unsupervised classification processes to develop final output analysis and classified maps.
Unlike most other resources on the web, we have experts from Universities around the country ready to answer your questions.
This resource area was created by the: community
Enter your zipcode to find your local Extension office:
Articles and Fact Sheets for Map@Syst
Map@Syst Geocoin Adventure
Application Areas
Additional Information
eXtension provides objective and research-based information and learning opportunities that help people improve their lives. eXtension is an educational partnership of 74 universities in the United States.
© 2008 eXtension. All rights reserved.
Comments
Subscribe to this page's comments
onogu jonathan on 08.23.08 at 03:09 PM
Post a comment about this topic