Skip to main content

An optimal image transform for threshold-based cloud detection using heteroscedastic discriminant analysis

Buy Article:

$63.00 plus tax (Refund Policy)

We present a simple image transform that optimally combines four image channels into a greyscale image for threshold-based cloud detection. These image channels, namely blue, green, red and near infrared, are present on many low Earth-orbit resource satellites. Applying a single threshold to a greyscale image is a computationally efficient method suitable for onboard implementation. We used heteroscedastic discriminant analysis (HDA), which is a generalization of the popular dimension-reducing linear discriminant analysis, to transform the image. Comparative tests between HDA, existing transforms from the remote-sensing literature (the haze optimized and D transforms), as well as the single red and blue image channels were conducted. Although thin clouds remain challenging for global threshold-based techniques, the HDA transform consistently gave the best average segmentation errors across the test dataset. This dataset consisted of 32 1 megapixel Quickbird and Landsat images. HDA has not previously been applied to remote-sensing data.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Document Type: Research Article

Affiliations: Department of Electrical and Electronic Engineering, Stellenbosch University, Stellenbosch, South Africa

Publication date: 2011-03-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect 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