| Popis: |
Image classification of satellite imagery interprets the thematic map to represent the spatial distribution of earth features. There are so many applications of Remote sensing image classification such as Resource utilization and environmental impact analysis etc. The overall process result depends on two main aspects (1) Every object have distinctive signature and feature of interest (2) The process can distinguish these features separately. Image classification is broadly classified in two ways (1) Hard classification and (2) Soft classification. In hard classification, pixels are classified in to a single class only and in soft classification, pixels can belong to one or more classes according to their membership values. In hard classification, data may lost because of the restriction being in a single class only. But in soft classification, this problem is resolved. But after resolving the problem, there is a need of accuracy assessment. There are many commercial software available in market but they are not providing accuracy assessment for soft classified images. So, in this study, a tool is designed to overcome such a problem. Keywords: Hard classification, Soft classification Fuzzy C-Means, Accuracy, Entropy |
