A fourth order P_Laplace underwater image restoration method based on MSG

Underwater imaging system has been widely applied in varieties and it is desired to recover underwater image using image processing techniques. In this paper, we proposed a fourth order P_Laplace underwater image restoration method based on MSG. Although the fourth order P_Laplace method has been proved that it could effectively reduce the gradient effect, the bright spot effect and color distortion still exist in the restored image especially when iterations increase. However, MSG model can be applied to solve this issue. The structure image is restored by the fourth order P_Laplace approach to recover the detailed information embedded in the blurred structure image. Then the texture and the restored structure image are recomposed to output the recovered image.

[1]  Tony F. Chan,et al.  High-Order Total Variation-Based Image Restoration , 2000, SIAM J. Sci. Comput..

[2]  Deepa Kundur,et al.  Blind image restoration via recursive filtering using deterministic constraints , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[3]  Deepa Kundur,et al.  Blind Image Deconvolution , 2001 .

[4]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[5]  Lu Fang,et al.  Image cartoon-texture decomposition using Mumford-Shah model and G-space , 2008 .

[6]  Mostafa Kaveh,et al.  Fourth-order partial differential equations for noise removal , 2000, IEEE Trans. Image Process..

[7]  Daniel Cremers,et al.  A convex representation for the vectorial Mumford-Shah functional , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  M. Kaveh,et al.  Image enhancement using fourth order partial differential equations , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).