CLASSIFICATION OF REMOTELY SENSED IMAGE USING RELEVANCE

This paper introduces a remotely sensed image classification method based on relevance vector machines (RVMs). The features of the remotely sensed image are extracted and the classification is done(4) with the help of those features. It is shown that approximately the good classification accuracy is obtained using RVM-based classification, with a significantly smaller relevance vector rate and, therefore, much faster testing time. This feature makes the RVM-based classification approach more suitable for applications that require low complexity and, possibly, real-time classification.