Membership function construction for interval-valued fuzzy sets with application to Gaussian noise reduction

摘要: Models based on interval-valued fuzzy sets make it possible to manage numerical and spatial uncertainty in grey-scale values of image pixels. In a recent paper, we proposed method that links the ultrafuzziness index (that makes take into account some uncertainty, like noise, inherent capture) with impulse noise removal. However, computing requires assigning their membership functions (MFs). The present article proposes novel for generation functions, histogram, remedy drawback complements our previous study. performance is evaluated by applying this technique particular case Gaussian detection reduction, which remains crucial issue processing. Experimental results have demonstrated leads filters are comparable well-known conventional filters, especially iterative filtering methods. Image details preserved while reducing link between thus verified. main advantage use basic information, namely an easy obtain.