We propose a double bilateral (DoBi) filter that consists of a classical bilateral filter and a new bilateral filter for image restoration. Bilateral filtering is a simple, noniterative, and effective denoising filter that smooths images while preserving edges by means of a nonlinear combination of adjacent pixel values. A median-metric weighting function is introduced by incorporating a switching median filter into the similarity function. This median-metric component associated with a spatial function constitute the second bilateral filter, which compensates the classical bilateral filter. Moreover, a parameter automation mechanism is proposed to facilitate the restoration procedure. A wide variety of images contaminated by various degrees of Gaussian, impulse, and mixed noise were used to assess the performance of this new restoration algorithm. Experimental results indicated that the DoBi filter outperformed several state-of-the-art methods in both visual image quality and restored signal quantity.