Saliency Detection Gradient Preservation for Bayer Image Color Reconstruction

Authors

  • TANG Chun-ming School of Artificial Intelligence Institute, Tianjin Polytechnic University, Tianjin, 300387, China
  • Hu Li-li School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin, 300387, China

Keywords:

Bayer image, Color correction, Four-direction weights, Residual interpolation, Saliency detection.

Abstract

Image color reconstruction is a necessary process to recover high quality full color images from Bayer images. In view of the existence of image texture and edge blurring in color reconstruction algorithms, a four-direction joint gradient weighted residual interpolation algorithm is proposed, which uses four-direction weights obtained from RGB pixel gradients and residual gradients in Bayer images, linearly combined with the color difference estimation to effectively obtain the full G image. Aiming at the color cast phenomenon of the image after color interpolation, a saliency detection gradient-preserving color correction algorithm is proposed based on the RGB image captured under natural light. Firstly, the saliency detection method is used to segment the interpolated image and the RGB image into two regions, then carrying out the region correspondence for gradient-preserving color correction, and finally the weighted fusion method is used to obtain the final color reconstructed image. The experimental results show that the reconstructed image texture and edges are clearer and the colors are closer to RGB images.

References

B.E. Bayer. “Color Imaging Array,” U.S. Patent 3 971 065, July. 20, 1976.

B.K. Gunturk, J. Glotzbach, Y. Altunbasak, R.W. Schafer and R.M. Mersereau. “Demosaicking: color filter array interpolation,” IEEE Signal Process Mag., vol. 22, pp. 44-54, Jan. 2005.

L. Zhang and X. Wu. “Color demosaicking via directional linear minimum mean square-error estimation,” IEEE Trans. Image Process., vol. 14, pp. 2167-2178, Dec. 2005.

I. Pekkucuksen and Y. Altunbasak. “Gradient based threshold free color filter array interpolation,” in Proc. IEEE Int. Conf. Image Process. (ICIP), 2010, pp. 137-140.

D. Kiku, Y. Monno, M. Tanaka and M. Okutomi. “Residual interpolation for color image demosaicking,” in Proc. IEEE Int. Conf. Image Process. (ICIP), 2013, pp. 2304-2308.

D. Kiku, Y. Monno, M. Tanaka and M. Okutomi. “Beyond Color Difference: Residual Interpolation for Color Image Demosaicking,” IEEE Trans. Image Process., vol. 25, pp. 1288-1300, Mar. 2016.

D. Kiku, Y. Monno, M. Tanaka and M. Okutomi. “Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking,” Sensors, vol. 17, pp. 2787-2807, Dec. 2017.

E. Reinhard, M. Ashikhmin, B. Gooch and P. Shirley. “Color Transfer between Images,” IEEE Computer Graphics and Applications, vol. 21, pp. 34-41, Oct. 2001.

C.H. Yao, C.Y. Chang and S.Y. Chien. “Example-based video color transfer,” IEEE International Conference on Multimedia and Expo(ICME), 2016, pp.1-6.

Z. Xie, S. Ding, B. Sheng, L. Ma. “Integrated tone and structure refinement for high-fidelity colour transfer,” Iet Image Processing, vol. 11, pp. 1281-1290, Oct. 2017.

M. Grogan and R. Dahyot. “L2 Divergence for robust colour transfer,” Computer Vision and Image Understanding, vol. 181, pp. 39-49, Feb. 2019.

J.F. Hamilton and J.E. Adams. “Adaptive color plan interpolation in single sensor color electronic camera,” U.S. Patent 5 629 734, May. 13, 1997.

S. Goferman, L. Zelnik-Manor and A. Tal. “Context-Aware Saliency Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, pp. 1915-1926, Oct. 2012.

I. Pekkucuksen and Y. Altunbasak. “Edge Strength Filter Based Color Filter Array Interpolation,” IEEE Trans. Image Process., vol. 21, pp. 393-397, Jan. 2012.

I. Pekkucuksen and Y. Altunbasak. “Multiscale Gradients-Based Color Filter Array Interpolation,” IEEE Trans. Image Process., vol. 22, pp. 157-165, Jan. 2013.

S.P. Jaiswal, O.C. Au, V. Jakhetiya, Y. Yuan and Y. Hai. “Exploitation of inter-color correlation for color image demosaicking,” in Proc. IEEE Int. Conf. Image Process. (ICIP), 2014, pp. 1812-1816.

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Published

2019-07-25

How to Cite

Chun-ming, T., & Li-li, H. (2019). Saliency Detection Gradient Preservation for Bayer Image Color Reconstruction. American Scientific Research Journal for Engineering, Technology, and Sciences, 58(1), 12–23. Retrieved from https://www.asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/4974

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Articles