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The authors have previously proposed a fuzzy stack filter that is defined by a fuzzy Boolean function. We have also presented a specific design method (called the fuzzy Boolean function determination method) for the most fundamental fuzzy stack filter, the FCWM (fuzzy center weighted median). By varying the fuzzy Boolean function, we can achieve both an arbitrary CWM filter and a weighted average value filter in which only the weights at arbitrary processing points are varied. Hence, in comparison with the CWM filter, our filter is better at eliminating Gaussian noise. In this paper, to improve the reconstruction accuracy of nonsteady state signals, such as the image signals, a data-dependent FCWM (DD-FCWM) is proposed anew. The data-dependent filter is an adaptive filter in which the filter parameters are varied in response to the nature of the data near the processing point (local information). In a DD-FCWM filter, the fuzzy Boolean function is varied by using local information. We demonstrate that the proposed DD-FCWM filter uses the local signal information to appropriately vary, not only the weights of the processing points, but also the filter mode (average value type or median type). Furthermore, by use of image processing examples, we demonstrate that highly accurate signal reconstruction can be attained. © 1998 Scripta Technica, Electron Comm Jpn Pt 3, 81(8): 27–40, 1998 [ABSTRACT FROM AUTHOR]