In this paper, we introduce a new color filter array interpolation based on edge map prediction using the Bayesian theorem. The edge information obtained at the position of the green component sampled in the quincunx grid using the Bayer pattern is used to predict the edge of the red and blue component positions distributed in the rectangular grid. In this process, the edge distribution of the entire image, local area, and nearest neighbors is analyzed to determine the smooth/edge characteristics stochastically. If the pixels at the red and blue positions are determined to be edge pixels, the edge direction is inherited from the edge pixels of the local region. By combining a new decision technique with directional weighted interpolation in the green plane reconstruction process, the interpolation accuracy can be improved compared with the existing demosaicking algorithms. After interpolating the green channel, the color difference between the interpolated green channel and the red/blue channel is used to refine the reconstructed green plane. The other color planes can then be interpolated using this refined green plane. Experimental results show that our algorithm improves both the objective and subjective image qualities compared with the conventional state-of-the-art demosaicking algorithms.
- Bayer pattern
- Bayesian theorem
- Color filter array interpolation
- decision-based interpolation
- edge map prediction