An landcover fuzzy logic classification by maximumlikelihood
This is an incremental improvement for remote sensing applications, potentially enhancing image classification in sectors like agriculture or environmental monitoring.
The paper tackles remote sensing image classification by combining maximum likelihood classification with fuzzy logic, experimenting with spatial, spectral, and texture methods for improved accuracy.
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.