Colour demosaicking for complementary colour filter array using spectral and spatial correlations

The complementary colour filter array (CCFA) that is widely used in consumer-level digital video cameras measures only one colour component per pixel, that is, cyan, magenta, yellow and green. To infer whole colour information at each pixel, a demosaicking process is required. However, most demosaicking methods proposed in the literatures were developed for the Bayer CFA, which has quite different pattern than the CCFA. This study presents a high quality edge-adaptive colour interpolation approach for the CCFA. Two estimates of the luminance signal are made at each pixel under different hypotheses on edge directions simply using bilinear interpolation. Not only the sampled signal but also these two estimates are employed to assist the final interpolation. A post-processing step for suppressing demosaicking artefacts by adaptive filtering is also presented. Experimental results confirm the performance of this algorithm both objectively and subjectively.