Superpixel based fusion and demosaicing for multi-focus Bayer images

Abstract In this paper, a novel superpixel based multi-focus image fusion algorithm for raw images of single-sensor color imaging devices which incorporates the Bayer pattern is proposed. The proposed algorithm is more efficient than traditional fusion schemes since the raw Bayer pattern images are fused before color demosaicing. With the proposed fusion algorithm, the interpolation errors introduced by the repeated demosaicing operation on multi-source images can also be greatly reduced. In detail, a clarity measurement of Bayer pattern image is defined to judge the focus-level of raw Bayer pattern images, and the fusion operator is performed on superpixels which provide powerful grouping cues of local image feature. By comparing the clarities of superpixels, a weight map is constructed and the guided filter is utilized to refine the weight map. The raw images are merged with refined weight map to get the fused Bayer pattern image, which is restored by the demosaicing algorithm to get the full resolution color image. Experimental results demonstrate that the proposed algorithm can obtain better fused results with more natural appearance and fewer artifacts than the traditional algorithms.