OPTIMAL FEATURE SELECTION FROM REMOTE SENSING IMAGES FOR AGRICULTURAL ACREAGE ESTIMATION

Feature extraction directly affect the classification process poor features leads to inaccurate classification results. Feature extraction is complex task when we classify any sort of data may be it textual data, simple image and complex image like remote sensing multispectral images. On the place of basic features used across the world, very specific features are used for crop classification in the agricultural field. Finding those relevant features out of available one is the first job on priority. Researcher used those features as an input for estimating agricultural acreage from remote sensing images. This can introduced the concept of feature dimension reductionality.