Abstract
In this paper, the concept of fuzzy transformation is developed based on fuzzy ordering theory. The clustering property of the fuzzy transformation is investigated by deriving the distribution function of the fuzzy samples and is exploited to address the DCT coded image deblocking problem. In this application, the fuzzy transformation is actually a highly data-adaptive smoothing and sharpening process. The spread parameter of the fuzzy transformation controls the smoothing level and can be optimized to fit images at different compression levels. The simulation results show that the fuzzy transformation can effectively remove various blocking artifacts and restore the original image monotone surfaces as well as edges with low computational complexity.