Structure tensor-based WLS filter for adaptive smoothing

Abstract

The weighted least squares (WLS) filter is a well-known edge preserving smoothing technique, but its weights highly depend on the image gradients. Thus, it is hard to smooth local textures with large gradients by WLS filter. In this paper, we propose a structure tensor-based WLS (ST-WLS) filter to enhance the smoothing ability of WLS filter while successfully keeping object boundaries. We introduce structure tensor into WLS filter to extract local structures in an image and use them to guide the smoothing process. Specifically, we use structure tensor to measure isotropy of pixels. Then, we calculate the smoothing weights for pixels based on both their isotropy and gradients. Experimental results demonstrate that ST-WLS filter has strong ability of smoothing textures, especially for isotropic textures, while preserving boundaries and structures of objects.