Defuzzification Strategies for Fuzzy Classifications of Remote Sensing Data

A Study on Hyperspectral Remote Sensing Classifications

In this paper, we discuss about hyperspectral image processing where it plays an important role in remote sensing, hyperspectral verses multispectral image processing and image classifications. Where these classifications includes image sensors, image preprocessing, object detection, object segmentation, feature extraction and object classification. Mainly there are two types of classifications...

Drought Analysis of Alvand Boundary River Using Remote Sensing Data

Extended abstract 1- Introduction       The study of the behavior of rivers in the arid and dry areas is one of the most important tasks in the country. Because the area has increased the effects of drought due to the sensitivity of the area and rainfall shortage, it causes changes in the flow and sediment regime, water resources, agriculture, and so on. Since plants react more precisely to t...

A Hierarchical Fuzzy Classification Scheme For Remote Sensing Data

Land covers mix and high input dimension are two important issues that affect the classification accuracy of remote sensing images. Fuzzy classification has been developed to represent the mixture of land covers. Two fuzzy classifiers of fuzzy rules-based (FRB) and fuzzy neural network (FNN) were studied to illustrate the interpretability of fuzzy classification. Based on the FNN classifier, a ...

Defuzzification of intuitionistic fuzzy sets

Defuzzification is the process of converting a fuzzy quantity to precise quantity, just as fuzzification is the conversion of a precise quantity to a fuzzy quantity. Various types of defuzzification methods, are available for conversion of fuzzy to non-fuzzy. In this paper, defuzzification functions in intuitionistic fuzzy environment such as triangular, trapezoidal, L-trapezoidal, R-trapezoida...

Defuzzification method for solving fuzzy linear systems