Content adaptive guided image filtering
Local filtering based edge-preserving smoothing technique could suffer from halo artifacts when it is applied for image enhancement. In this paper, an adaptive guided image filter is proposed by incorporating edge aware weighting which is derived from normalized local variance of a guidance image into an existing guided filter. It is shown that the proposed filter preserves sharp edges better than the existing guided filter. With the observation, it is applied for tone mapping of high dynamic range images and fusion of differently exposed images. Experimental results show that the resultant tone mapping and exposure fusion algorithms can prevent halo artifacts from appearing in the final images.