We propose an image sharpening method that automatically optimizes the perceived sharpness of an image. Image sharpness is defined in terms of the one-dimensional contrast across region boundaries. Regions are automatically extracted for all natural scales present that are themselves identified automatically. Human judgments are collected and used to learn a function that determines the best sharpening parameter values at an image location as a function of certain local image properties. Experimental results demonstrate the adaptive nature and superior performance of our approach.

• M. Nam, N. Ahuja, Learning Human Preferences to Sharpen Images, ICPR 2012 Tsukuba, Japan, November 2012.