Land cover classification using fuzzy rules and aggregation of contextual information through evidence theory

Land cover classification using multispectral satellite image is a very challenging task with numerous practical applications. We propose a multi-stage classifier that involves fuzzy rule extraction from the training data and then generation of a possibilistic label vector for each pixel using the fuzzy rule base. To exploit the spatial correlation of land cover types we propose four different information aggregation methods which use the possibilistic class label of a pixel and those of its eight spatial neighbors for making the final classification decision. Three of the aggregation methods use Dempster-Shafer theory of evidence while the remaining one is modeled after the fuzzy k-NN rule. The proposed methods are tested with two benchmark seven channel satellite images and the results are found to be quite satisfactory. They are also compared with a Markov random field (MRF) model-based contextual classification method and found to perform consistently better.Comment: 14 pages, 2 figure

The designed synthesis, recognition, and possible applications of Zn(III) complex

The structural pressure-induced ionization process is implemented to produce Zn(III) complex for the first time and possible potential applications for technological advances are reported in this article. The inversion of the electron population observed at the ground state of the newly synthesized complex corroborates an unexplored material response property towards electrical and magnetic fields. The first-time report of a true transition metal behavior of zinc fetches new thoughts about zinc-based bio-enzymatic and bio-catalytic processes along with its material applications in untouched files like live cell imaging contrast agents, photocatalytic water splitting, etc. The methodology of the ‘ structural pressure-induced ionization process’ may be implemented for the synthesis of more unusual oxidation states of metals