Simple and Efficient Soft Morphological Filter in Periodic Noise Reduction
Zhen Ping Ji, Huilian Liao, Xijun Zhang, Qinghua Wu · 2006
In this paper, a simple and efficient soft morphological filter (SMF) regarded as the extension of the standard morphological operators, is proposed for reducing the periodic noise in images. Since the SMF performs better in details preserving than other conventional spatial filters, the filtering quality of SMF is improved significantly to a desirable level the same as the frequency filters do. The SMF, as a spatial method, shows its significant advantage of computation simplicity in comparison with the frequency filters. Meanwhile, the definition of structuring elements used in the SMF is much simpler than that of the frequency filters' parameters. Simulation results show that the SMF is able to reduce periodic noise more effectively than other known approaches