Superpixel-Guided Adaptive Image Smoothing

In edge-preserving image smoothing, edge blurriness and structural edge attenuation have been common problems. L0 smoothing successfully solves these two problems by adopting L0 norm of gradients. However, a weak structural edge diminishing problem still exists because L0 penalty first removes small nonzero gradients. In order to address this problem, we propose superpixel-guided adaptive image smoothing by introducing an adaptive parameter into L0 smoothing framework. The adaptive smoothing parameter is efficiently computed in a cascade manner. In the first stage, we allocate smoothing parameters to the pixels consisting of details. More importantly, we then exploit similarities between a pixel and its surrounding superpixels for assigning smoothing parameters to the rest pixels. Experimental results demonstrate that our proposed method efficiently preserves structural edges regardless of their scales compared to previous methods.