在這篇論文中，我們提出了一可適性色彩內插演算法用於單一感測元件的取像裝置。為了減少數位取像裝置的成本及體積，消費型數位相機常藉著使用單一感測元件來攝取影像。色彩濾鏡陣列通常被使用於這些單一感測元件取像裝置上，根據貝爾排列模式相對的位置分別對三原色的像素值取樣，而計算取像過程中丟失的像素值的過程被叫做色彩內插演算法。我們針對貝爾排列模式的色彩濾鏡陣列提出一個有效且快速的色彩內插演算法。我們所提出的演算法利用更佳的初始演算法，減少因疊代策略所產生之拉鏈型效應，再以不同色彩平面訊號相關性為基礎來估算丟失的像素，並且經由疊代的方法逐漸修正像素值，如此可獲得較高之PSNR值，也就是可獲得更佳的重建影像品質。本研究另一個貢獻是使用可適性邊界判斷，以垂直或水平之G-R或G-B做最後之像素值修正，可以更快獲得快速收歛的像素值，並且大幅節省所需之運算量。實驗結果顯示我們提出之演算法重建之影像品質較佳並且可大幅降低所需之計算複雜度。

This research aims to present an adaptive demosaicing algorithm for Bayer pattern images of single-sensor digital still cameras. The proposed algorithm uses an iterative strategy to update the values of color planes. Although the iterative strategies are capable of achieving higher image quality in the demosaiced image, its computation is still too much. In order to reduce computational complexity, an improved initial interpolation is suggested to reduce the zipper effects of a demosaiced image and an adaptive refinement interpolation is suggested to speed up the execution of demosaicing. Experiment results indicate that the PSNRs of the proposed method are higher than the state-of-the-art demosaicing methods. Furthermore, the computational cost of the proposed method is less than that of previous iterative algorithms.

[1] B. E. Bayer, “Color imaging array,” U.S. Patent 3 971 065, July 1976.
[2] H. S. Hou et al., “Cubic splines for image interpolation and digital filtering,” IEEE Trans. Acoust., Speech, Signal Process, Vol. ASSP-26, No.3, pp. 508–517, June 1987.
[3] T. Kuno and H. Sugiura, “New interpolation method using discriminated color correlation for digital still cameras,” IEEE Trans. Consumer Electron, Vol. 45, No. 1, pp. 259–267, Feb. 1999.
[4] S. C. Pei and I.-K. Tam, “Effective color interpolation in CCD color filter array using signal correlation,” IEEE Trans. Circuits and Systems for Video Technology, Vol. 13, No. 6, pp. 503–513, June 2003.
[5] J. E. Adams Jr., “Interactions between color plane interpolation and other image processing functions in electronic photography,” Proc. SPIE, vol.2416, pp. 144–151, Feb. 1995.
[6] J. Adams, K. Parsulski, and K. Spaulding, “Color processing in digital cameras,” IEEE Micro, pp. 20–29, Nov.–Dec. 1998.
[7] J. F. Hamilton Jr. and J. E. Adams, “Adaptive color plane interpolation in single color electronic camera,” U.S. Patent 5 629 734, May 1997.
[8] P. S. Tsai, Tinku Acharya, Ajay K.Ray, “Adaptive Fuzzy Color Interpolation,” Journal of Electronic Imaging, Vol. 11, pp. 1-24, July 2002.
[9] R. Kimmel, “Demosaicing: Image reconstruction from color CCD samples,” IEEE Trans. Image Processing, Vol. 8, pp. 1221–1228, Sept. 1999.
[10] W. Lu and Y.-p. Tan, “Color filter array demosaicing: New method and performance measures,” IEEE Trans. Image Process, Vol. 12, No. 10, pp. 1194–1210, Oct. 2003.
[11] B. K. Gunturk, Y. Altunbasak, and R. M. Mersereau, “Color plane interpolation using alternating projections,” IEEE Trans. Image Process, Vol. 11, No. 9, pp. 997–1013, Sep. 2002.
[12] Xin Li, “Demosaicing by Successive Approximation,” IEEE Trans. Image Process, Vol. 14, No. 3, pp.370–379, Mar. 2005.
[13] T. W. Freeman, “Median Filter for Reconstructing Missing Color Samples,” U.S. Patent 4 724 395, 1988.
[14] M. D. Fairchild, Color Appearance Models. Reading, MA: Addison-Wesley, 1997.
[15] J. E. Adams Jr., “Design of color filter array interpolation algorithms for digital cameras, Part 2,” IEEE Int. Conf. Image Processing, Vol.1, pp. 488–492, Oct. 1998.
[16] C. A. Laroche and M. A. Prescott, “Apparatus and method for adaptively interpolating a full color image utilizing chrominance gradients,” U.S. Patent 5 373 322, 1994.
[17] J. Allebach and P. W. Wong, “Edge-directed interpolation,” IEEE Int. Conf. Image Processing, Vol. 3, pp. 707–710, 1996.
[18] W. K. Pratt, Digital Image Processing, 3rd Ed. New York, NY: Wiley, 2001.
[19] http://www.mathworks.com/index.shtml