An landcover fuzzy logic classification by maximumlikelihood

TL;DR

This paper explores a land cover classification method combining fuzzy logic with maximum likelihood to improve remote sensing image analysis, experimenting with spatial and spectral texture techniques.

Contribution

It introduces a novel integration of fuzzy logic with maximum likelihood classification for remote sensing images, incorporating spatial and spectral texture methods.

Findings

Enhanced classification accuracy with fuzzy logic integration

Effective use of spatial and spectral texture methods

Potential for improved remote sensing image analysis

Abstract

In present days remote sensing is most used application in many sectors. This remote sensing uses different images like multispectral, hyper spectral or ultra spectral. The remote sensing image classification is one of the significant method to classify image. In this state we classify the maximum likelihood classification with fuzzy logic. In this we experimenting fuzzy logic like spatial, spectral texture methods in that different sub methods to be used for image classification.