Fast image interpolation using the bilateral filter

In this study, the authors propose a new image interpolation technique using the bilateral filter to estimate the unknown high-resolution pixels. Compared with the least-squares estimation, a small-kernel bilateral filter has the advantages of fast computation and stability. The range distance of the bilateral filter is estimated using a novel maximum a posterior estimation, in order to consider both the diagonal and vertical-horizontal correlations. For the consideration of global consistency, the pixel-based soft-decision estimation (SAI) is proposed to constrain the consistency of edge statistic within a local window. Experimental results show that the interpolated images using the proposed algorithm give an average of 0.462, 0.413, 0.532 and 0.036-dB peak signal-to-noise ratio (PSNR) improvement compared with that using the bicubic interpolation, linear minimum mean squares error estimation, new edge-directed interpolation (NEDI) and SAI respectively. The subjective quality agrees with the PSNR as well. More importantly, the proposed algorithm is fast and it requires around 1/60 computational cost of the SAI.