The removal of additive noise in digital images is currently a subject of intense interest. Recent research has shown that to be effective the filter should adapt itself to the local structure existing in the image: In regions which have no dominant structure the adaptive filter should act as a linear statistics filter while in regions with a strong or dominant structure the adaptive filter should act as an ordered statistics filter. In the past the adaptive filters worked in a discontinuous mode by switching between a linear statistic Ε½ . filter used when the local region has no dominant structure and an ordered statistic Ε½ . filter used when the local region had a strong structure . In this case, the adaptation mechanism is separate from the noise smoothing algorithm and is usually ad hoc. In this paper we describe a new fuzzy filter in which the adaptation mechanism is no longer ad hoc: instead it is integrated into the noise smoothing algorithm. In addition, the adaptation mechanism works in a continuous modeαchanging gradually as we move from a local region with no dominant structure to a local region with a strong dominant structure.