Abstract

Images contain many levels of important structures and edges. Compared to masses of research to make filters edge preserving, finding scale-aware local operations was seldom addressed in a practical way, al- beit similarly vital in image processing and computer vision. We propose a new framework to filter images with the complete control of detail smooth- ing under a scale measure. It is based on a rolling guidance implemented in an iterative manner that converges quickly. Our method is simple in imple- mentation, easy to understand, fully extensible to accommodate various data operations, and fast to produce results. Our implementation achieves realtime performance and produces artifact-free results in separating dif- ferent scale structures. This filter also introduces several inspiring proper- ties different from previous edge-preserving ones.