Adaptive image processing using rank-order filters with spatial connectivity of elements

A new approach to design rank-order filters based on an explicit use of spatial relations between image elements is proposed. Many rank-order processing techniques may be implemented by applying the approach, such as noise suppression, local contrast enhancement, and local detail extraction. The performance of the proposed rank-order filters for suppression a strong impulsive noise in a test interferogram-like image is compared to conventional rank-order algorithms. The comparisons are made using a mean square error, a mean absolute error, and a subjective human visual error criteria.