A New Class of Detail-Preserving Filters for Image Processing

Abstract

A new class of median type filters for image processing is proposed. In the filters, linear FIR substructures are used in conjunction with the median operation. The root signals and noise attenuation properties of the FIR-median hybrid filters are analyzed and compared to representative edge preserving filtering operations. The concept of multilevel median operation is introduced to improve the detail preserving property of conventional median and the FIR-median hybrid filters. In the multilevel filters there exists a tradeoff between noise attenuation and detail preservation. The analysis and examples indicate that FIR-median hybrid filters preserve details better and are computationally much more efficient than the conventional median and the K-nearest neighbor averaging filters.