Non-linear scale-space based on fuzzy sharpening
Carlos López-Molina, Nicolás Madrid · 2017
This work explores a novel image enhancement operator based on a fuzzy-numerical description of images. Subsequently, the work analyzes the scale-space created by iteratively applying it to grayscale images; the novel scale-space is, hence, governed by the number of iterations the sharpening process is carried out. Finally, the effects of our proposal are illustrated in both 1D signals and grayscale images.