Abstract

Covering sensor surface with a Color Filter Array (CFA) and enabling a sensor pixel sample only one of three primary color values, is how single sensor digital cameras capture imagery. An interpolation process, called CFA demosaicking estimates other two missing color values at every pixel to render a full color image. This study presents two contributions to CFA demosaicking: a new and improved CFA demosaicking method to ensure high quality color images and new image measures to quantify demosaicking performance. Though digital cameras are now more powerful and smaller, Charge-Coupled Device (CCD) sensors continue to associate only one color to a pixel. Called Bayer Pattern this color mosaic is processed to get a high resolution color image. Every interpolated image pixel includes a full surrounding pixels colors based color spectrum. This study uses an edge indicator function and edge directions are considered in the suggested interpolation method to avoid high frequency region artifacts and improve performance.

Keywords:

Bayer pattern, Color Filter Array (CFA), demosaicking , fuzzy logic , genetic algorithm,

References

1. Aleksic, M. and R. Lukac, 2004. Local correlation based CFA interpolation. Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering, 2: 793-796.
   CrossRef    
2. Andriantiatsaholiniaina, L.A., V.S. Kouikoglou and Y.A. Phillis, 2004. Evaluating strategies for sustainable development: Fuzzy logic reasoning and sensitivity analysis. Ecol. Econ., 48(2): 149-172.
   CrossRef    
3. Bai, Y. and D. Wang, 2010. On the comparison of fuzzy interpolation and other interpolation methods in high accuracy measurements. Proceeding of IEEE International Conference on Fuzzy Systems (FUZZ), pp: 1-7.
   CrossRef    PMCid:PMC3023275    
4. Baranyi, P., L.T. Kóczy and T.D. Gedeon, 2004. A generalized concept for fuzzy rule interpolation. IEEE T. Fuzzy Syst., 12(6): 820-837.
   CrossRef    
5. Bayer, B.E., 1976. Color Imaging Array. U.S. Patent No. 3,971,065. U.S. Patent and Trademark Office, Washington, DC.
   
6. Benz, U.C., P. Hofmann, G. Willhauck, I. Lingenfelder and M. Heynen, 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS J. Photogramm., 58(3): 239-258.
   CrossRef    
7. Boriskin, A.V. and R. Sauleau, 2010. Hybrid genetic algorithm for fast electromagnetic synthesis. Proceeding of International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves (MSMW 2010), pp: 1-4.
   CrossRef    
8. Chandrasekhar, G., B.A. Rahim, F. Shaik and K.S. Rajan, 2010. Ricean code based compression method for Bayer CFA images. Proceeding of the Recent Advances in Space Technology Services and Climate Change (RSTSCC, 2010), pp: 102-106.
   CrossRef    
9. Chen, Z. and G. Chen, 2007. An adaptive weighting approach for image color and magnitude interpolation. Proceeding of International Conference on Consumer Electronics (ICCE, 2007), pp: 1-2.
   CrossRef    
10. Chung, K.H. and Y.H. Chan, 2006. An adaptive color filter array interpolation algorithm for digital camera. Proceeding of IEEE International Conference on Image Processing, pp: 2697-2700.
    CrossRef    
11. Dillon, P.L., D.W. Lewis and F.G. Kaspar, 1978. Color imaging system using a single CCD area array. IEEE T. Electron. Dev., 25: 102-107.
    CrossRef    
12. El-Mihoub, T.A., A.A. Hopgood, L. Nolle and A. Battersby, 2006. Hybrid genetic algorithms: A review. Eng. Lett., 13(2): 124-137.
    
13. Fuller, S.D., S.J. Butcher, R.H. Cheng and T.S. Baker, 1996. Three-dimensional reconstruction of icosahedral particles-the uncommon line. J. Struct. Biol., 116(1): 48-55.
    CrossRef    PMid:8742722    
14. García-Martínez, C. and M. Lozano, 2008. Local search based on genetic algorithms. In: Advances in Metaheuristics for Hard Optimization. Springer, Berlin, Heidelberg, pp: 199-221.
    CrossRef    
15. Gunturk, B.K., J. Glotzbach, Y. Altunbasak, R.W. Schafer and R.M. Mersereau, 2005. Demosaicking: Color filter array interpolation. IEEE Signal Proc. Mag., 22(1): 44-54.
    CrossRef    
16. Hua, L., L. Xie and H. Chen, 2010. A color interpolation algorithm for Bayer pattern digital cameras based on green components and color difference space. Proceeding of IEEE International Conference on Progress in Informatics and Computing (PIC, 2010), 2: 791-795.
    
17. Hubel, P.M., J. Liu and R.J. Guttosch, 2004. Spatial frequency response of color image sensors: Bayer color filters and Foveon X3. In: Electronic Imaging 2004 Anonymous (International Society for Optics and Photonics, 2004), pp: 402-407.
    CrossRef    
18. Kim, C.W. and M.G. Kang, 2005. Noise insensitive high resolution demosaicing algorithm considering cross-channel correlation. Proceeding of IEEE International Conference on Image Processing (ICIP, 2005), 3: III-1100-3.
    
19. Koczy, L.T. and K. Hirota, 1997. Size reduction by interpolation in fuzzy rule bases. IEEE T. Syst. Man Cy. B, 27(1): 14-25.
    CrossRef    PMid:18255836    
20. Kuan, D.T., A.A. Sawchuk, T.C. Strand and P. Chavel, 1985. Adaptive noise smoothing filter for images with signal-dependent noise. IEEE T. Pattern Anal., 2: 165-177.
    CrossRef    
21. Lukac, R. and K.N. Plataniotis, 2004a. Normalized color-ratio modeling for CFA interpolation. IEEE T. Consum. Electr., 50(2): 737-745.
    CrossRef    
22. Lukac, R. and K.N. Plataniotis, 2004b. An efficient CFA interpolation solution. Proceedings of 46th International Symposium on Electronics in Marine, pp: 543-548.
    
23. Lukac, R. and K.N. Plataniotis, 2005a. Data adaptive filters for demosaicking: A framework. IEEE T. Consum. Electr., 51(2): 560-570.
    CrossRef    
24. Lukac, R. and K.N. Plataniotis, 2005b. Fast video demosaicking solution for mobile phone imaging applications. IEEE T. Consum. Electr., 51(2): 675-681.
    CrossRef    
25. Lukac, R. and K.N. Plataniotis, 2005c. Universal demosaicking for imaging pipelines with an RGB color filter array. Pattern Recogn., 38(11): 2208-2212.
    CrossRef    
26. Lukac, R. and K.N. Plataniotis, 2005d. Color filter arrays: Design and performance analysis. IEEE T. Consum. Electr., 51(4): 1260-1267.
    CrossRef    
27. Lukac, R., B. Smolka, K. Martin, K.N. Plataniotis and A.N. Venetsanopoulos, 2005. Vector filtering for color imaging. IEEE Signal Proc. Mag., 22(1): 74-86.
    CrossRef    
28. Lulé, T., S. Benthien, H. Keller, F. Mutze, P. Rieve, K. Seibe and M. Bohm, 2000. Sensitivity of CMOS based imagers and scaling perspectives. IEEE T. Electron. Dev., 47(11): 2110-2122.
    CrossRef    
29. Mantere, T. and J.T. Alander, 2001. Testing half toning methods by images generated by genetic algorithms. Arpakannus, 1: 39-44.
    
30. Moller, T., R. Machiraju, K. Mueller and R. Yagel, 1997. Evaluation and design of filters using a Taylor series expansion. IEEE T. Vis. Comput. Gr., 3(2): 184-199.
    CrossRef    
31. Nallaperumal, K., S.S. Vinsley, S. Christopher and R.K. Selvakumar, 2007. A novel adaptive weighted color interpolation algorithm for single sensor digital camera images. Proceeding of International Conference on Computational Intelligence and Multimedia Applications, 3: 477-481.
    CrossRef    
32. Naveen, L., B. Shobanbabu and M. Tech, 2013. Color filter array interpolation for edge strength filters. Int. J. Eng. Trends Technol. (IJETT), 4(7): 2774-2778.
    
33. Park, S.W. and M.G. Kang, 2004. Color interpolation with variable color ratio considering cross-channel correlation. Opt. Eng., 43(1): 34-43.
    CrossRef    
34. Parmar, M. and S.J. Reeves, 2004. A perceptually based design methodology for color filter arrays [image reconstruction]. Proceedings of International Conference on Acoustics, Speech and Signal Processing (ICASSP'04), 3: iii-473-6.
    
35. Parulski, K. and K.E. Spaulding, 2003. Color Image Processing for Digital Cameras. In: Sharma, E. (Ed.), Digital Color Imaging Handbook. CRC Press/Taylor and Francis, Boca Raton/Florida, pp: 727-757.
    
36. Roubos, J.A., M. Setnes and J. Abonyi, 2003. Learning fuzzy classification rules from labeled data. Inform. Sci., 150(1): 77-93.
    CrossRef    
37. Smith, M.R. and S.T. Nichols, 1988. Efficient algorithms for generating interpolated (zoomed) MR images. Magn. Reson. Med., 7(2): 156-171.
    CrossRef    PMid:3398763    
38. Tan, Y., G.Z. Tan and X.D. Wu, 2011. Hybrid real-coded genetic algorithm with chaotic local search for global optimization [J]. J. Inform. Comput. Sci., 8(14): 3171-3179.
    
39. Thakur, R.K., A. Tripathy and A.K. Ray, 2009. A design framework of digital camera images using edge adaptive and directionally weighted color interpolation algorithm. Proceeding of International Joint Conference on Computational Sciences and Optimization (CSO, 2009), pp: 905-909.
    CrossRef    
40. Thévenaz, P. and M. Unser, 1997. Separable least-squares decomposition of affine transformations. Proceeding of IEEE International Conference on Image Processing, pp: 26-29.
    
41. Tsai, P.S., T. Acharya and A.K. Ray, 2002. Adaptive fuzzy color interpolation. J. Electron. Imaging, 11(3): 293-305.
    CrossRef    
42. Unser, M., A. Aldroubi and M. Eden, 1995. Enlargement or reduction of digital images with minimum loss of information. IEEE T. Image Process., 4(3): 247-258.
    CrossRef    PMid:18289976    
43. Walia, E. and C. Singh, 1993. An analysis of linear and non-linear interpolation techniques for three-dimensional rendering. Proceeding of Geometric Modeling and Imaging--New Trends, pp: 69-76.
    
44. Weinhaus, F.M. and V. Devarajan, 1997. Texture mapping 3D models of real-world scenes. ACM Comput. Surv., 29(4): 325-365.
    CrossRef    
45. Wu, X. and N. Zhang, 2004. Primary-consistent soft-decision color demosaicking for digital cameras (patent pending). IEEE T. Image Process., 13(9): 1263-1274.
    CrossRef    PMid:15449587    
46. Yamanaka, S., 1977. Solid State Color Camera. U.S. Patent No. 4,054,906. U.S. Patent and Trademark Office, Washington, DC.
    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.