Multi-Feature Processing Techniques with Information Mining From Remote Sensing Images

J.V.D. Prasad, Babu Sallagundla and A. Raghuvira Pratap

The sequence of control outlining and multi-features of the remote sensing images and processing techniques are getting advanced day by day. Removing different inner features of moderately homogeneous raw images utilizing a image segmentation calculation need to be performed. In this paper, Multi-Feature Remote Sensing (MFRS) algorithm is proposed which is used for processing multi-features of satellite remote sensing data. In the first place, the development of a new model structure for changed data recovery from a remote sensing database is proposed. At the second point, as the objective substance can't be communicated by one sort of features alone, a different component included recovery method is proposed. Thirdly, a model framework that was a novel technique for gaining transformation discovery of data from remote sensing images thus can reduce the requirement for image pre-handling and furthermore manage issues identified with occasional changes and additionally different issues experienced in the field of progress identification. In the mean time, the new model has imperative consequences for enhancing remote sensing image administration and self-governing data recovery. The test results acquired utilizing a LANDSAT informational collection and to prove that the utilization of the new model can deliver promising outcomes.

Volume 11 | Issue 12

Pages: 97-106

DOI: 10.5373/JARDCS/V11I12/20193217