Image smoothing via a scale-aware filter and L0 norm

Abstract

It is difficult to preserve diminishing weak structures and edges, and remove complex details simultaneously in the context of image smoothing. While most of existing methods only take either local or global features into consideration, the authors propose two methods taking advantage of both to achieve smoothing, both of which consist of two steps and share the same first step. In the first step, the authors use a scale-aware approach to generate a guidance image by blurring the smallscale components in the input image. Such approach, based on the rolling guidance framework with domain transform filter and bilateral filter, can prevent diminishing the corners of the main structures. Subsequently, the authors use the two proposed methods, with the guidance image as input, to remove blurry details. The first method introduces two data fidelity terms into L0 gradient minimisation and removes high-contrast details, which is a structure-preserving method. The other method, an edgepreserving method, uses an adaptive L0 gradient minimisation technique, facilitating the preservation of the weak structures and edges. The smoothing factors in such technique are decide by the corresponding gradient of each pixel of the guidance image. The authors apply both methods to various image processing fields.