Color demosaicking using deinterlacing and median-based filtering techniques

Abstract

Color demosaicking is critical to the image quality of single-sensor-based imaging devices. Caused by the sampling pattern of color filter array (CFA), the demosaicked images typically suffer from visual color artifacts in regions of high frequency and sharp edge structures, degrading the quality of camera output. We present a new high-quality demosaicking algorithm by taking advantage of deinterlacing and median-based filtering techniques. We treat the sampled green data of Bayer CFA as a form of diagonal interlaced green planes and make use of some key concepts about spatial deinterlacing to help the edge estimation in terms of both various directions and accuracy. In addition, a specific edge feature, sharp line edge of width 1 pixel, can also be handed well by the proposed method. The median-based filtering techniques are developed for suppressing most visual demosaicking artifacts, such as zipper effect, false color artifact, and interpolation artifact. Experimental results show that our algorithm is effective in suppressing visual artifacts, preserving the edges of image with sharpness and satisfying visual inspection, while keeping computational efficiency.