A novel Adaptive class of Decision based Non-linear Rank-ordered Filters for the Restoration of Impulse corrupted digital images

The thesis presents a novel adaptive class of decision based non-linear rank-order filter operators equipped with a variety of distinct characteristics to deal salt & pepper impulse noise situations in digital images even those which consume 95% signal content. The filters more efficiently choose an appropriate impulse restorer by adaptively moving over an acceptable image space to retain sharp details with least blocky, patchy effects.