Abstract :
With the continued growth of multimedia and communications systems, the instrumentation and measurement fields have seen a steady increase in the focus on image data. Developing tools and techniques to enhance the quality of image data plays a very relevant role. Enhancement of noisy images, however, is not a trivial task. The filtering action should distinguish between unwanted noise (to be removed) and image details (to be preserved or possibly enhanced). Nonlinear filters based on fuzzy systems effectively complete this task, outperforming conventional methods. Fuzzy reasoning is very well suited to model the uncertainty that typically occurs when both noise cancellation and detail preservation represent very critical issues. Since 1992, the number of different approaches to fuzzy filtering has been progressively increasing. The goal of this article is to explain the basic principles of fuzzy filtering, focusing on a selection of the most significant methods
Keywords :
filtering theory; fuzzy systems; image enhancement; nonlinear filters; detail preservation; fuzzy filtering; fuzzy reasoning; fuzzy techniques; image enhancement; noise cancellation; noisy images; nonlinear filters; uncertainty; Filtering; Fuzzy reasoning; Fuzzy systems; Image enhancement; Instrumentation and measurement; Multimedia communication; Multimedia systems; Noise cancellation; Nonlinear filters; Uncertainty;