Recursive image filters are computationally more efficient than nonrecursive ones. The phase of recursive filters is normally nonlinear, but it can become linear (actually zero) by the use of multi-directional filtering, in which the overall system is a cascade or parallel combination of the same simple recursive filter applied in different directions. The same concept is generalized to include nonlinear recursive multi-directional image filters. Non-linear recursive filters have not been investigated in the literature due to their analytic difficulty and their lack of general stability criteria. A useful task requiring nonlinear operation is to differentiate the high spatial frequency components of a picture into those due to edges and those due to noise. A linear low-pass filter will simultaneously smooth noise and blur edges. A linear high-pass filter will simultaneously crisp edges and enhance noise. We propose a specific nonlinear multi-directional recursive scheme for simultaneous edge enhancement and noise smoothing of images. The filter has low complexity and is guaranteed to be stable. It can be used for image enhancement or restoration purposes, or as a pre-processor for spatial coding techniques, in which case the compression ratio can be increased without deterioration of quality by eliminating useless information form the original signal.