A Fuzzy Method for Increasing the Contrast of Low-Quality Cartographic Images

In this study, we have developed a new image enhancement method that uses fuzzy logic. This method allows us to split pixel values into different levels of importance, which helps to compensate for the loss of local brightness in dark and bright areas of an image. The goal is to increase the overall brightness of the image while preserving details. The process involves three stages. Firstly, the satellite image is transformed into a membership space using the c-means clustering algorithm. This creates a model that can be used to convert each pixel value into a level of importance. Secondly, a corresponding model is created for each level of importance based on the membership data. Finally, the image is transformed back into a standard brightness space by combining the grayscale values for each level. Our results show that this method improves the visual quality and accuracy of measurements when compared to traditional methods.