A hybrid histogram/neural network classifier for creating global cloud masks

$59.35 plus tax (Refund Policy)

Buy Article:


Abstract. A histogram method is used to identify the features which are used to classify the scene elements, and a hierarchical neural network with 'don`t care` nodes is used to perform the actual classification. Although the ultimate goal is to produce a classifier capable of detecting clouds anywhere in the world, this preliminary system is limited to classifications in three distinct ecosystems: the polar region, desert terrain, and scenes of biomass burning in South America. Classification accuracies of 97.5 per cent for desert data, 98 per cent for polar data, and 99.2 per cent for biomass burning data were achieved. More importantly, manual analysis of classified scenes which had not been previously seen by the classifier show 'very good` to 'excellent` correspondence between the computer generated classifications and the human expert classifications.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/014311697218791

Publication date: March 10, 1997

More about this publication?
Related content

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more