# Fuzzy Rules and Evidence Theory for Satellite Image Analysis

Source: [Fuzzy Rules and Evidence Theory for Satellite Image Analysis](<https://www.sota2.com/research/paper/68fa603f1e209131ce9ee696>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T19:35:40.298Z

Authors: Arijit Laha, J. Das

Published: 2011-04-08T05:18:15.000Z

## Abstract

Design of a fuzzy rule based classifier is proposed. The performance of the classifier for multispectral satellite image classification is improved using Dempster- Shafer theory of evidence that exploits information of the neighboring pixels. The classifiers are tested rigorously with two known images and their performance are found to be better than the results available in the literature. We also demonstrate the improvement of performance while using D-S theory along with fuzzy rule based classifiers over the basic fuzzy rule based classifiers for all the test cases.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1104.1485>)

[PDF](<https://arxiv.org/pdf/1104.1485.pdf>)
