Abstract
Fuzzy techniques can be applied in several domains of image processing. In this paper we will give a survey on how fuzzy similarity measures can be used in establishing measures for image comparison. Objective quality measures or measures of comparison are of great importance in the field of image processing. These mea- sures serve as a tool to evaluate and to compare different algorithms designed to solve particular problems, such as noise reduction, de- blurring, compression, ... Consequently these measures serve as a basis on which one algorithm is preferred to another. Furthermore, it is well-known that classical quality measures, such as the RMSE (Root Mean Square Error) or the PSNR(Peak Signal to Noise Ra- tio), do not always correspond to visual observations.
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