Fuzzy pixel decomposition approach in classification of Remote Sensing data
Tsukasa Hosomura, Pan Rui
Computer Science Division
Asian Institute of Technology
G.P.O. Box 2754, Bangkok 10501, Thailand
Abstract
In the conventional remote sensing classification, most classification results are represented in a one-pixel-one-class mapping in which a pixel is a indivisible minimum unit no matter whether it is class mixture pixel or not, which greatly and always limits the improvement of classification and boundary accuracies.
This work describes a new approach of using fuzzy pixel decomposition algorithm in which each pixel is represented as a fuzzy pixel and then divided into sub-pixels. The algorithm consists of two major steps: Pixel membership grade analysis, and Pixel decomposition, in which fuzzy set theory is applied for identifying the land cover membership grade of each pixel, and neighborhood window is used for identifying the position of each sub-pixel. The identification and positioning of each sub-pixel improve the extraction of spectral information and then achieve higher classification and boundary accuracies.
Results of classifying TM and MOS-1 images of Thailand are presented and their accuracies are analyzed.
