Normal curvature-induced variational model for image restoration

作者：Liu, Pengfei^*; Xiao, Liang; Li, Tao

来源：IET Image Processing, 2018, 12(5): 679-689.

DOI：10.1049/iet-ipr.2017.0603

• variational techniques
• image restoration
• cellular biophysics
• medical image processing
• normal curvature-induced variational model
• image surface normal curvature prior information
• normal curvature-induced higher-order regulariser
• alternating direction method of multipliers technique
• natural images
• biomedical cell images
• peak-signal-to-noise ratio
• convergence rate
• restoration quality

In this study, a novel normal curvature-induced variational model which involves a higher-order regulariser based on the normal curvature prior information of image surface is proposed for image restoration. Furthermore, the authors derive a preferably equivalent formulation for the proposed normal curvature-induced higher-order regulariser. Then, they design an efficient algorithm to solve the proposed model by using the famous alternating direction method of multipliers technique. Finally, they assess the performance of the proposed method on both natural images and biomedical cell images by comparing it with the famous fast total variation (TV) method, fractional-order TV method and Hessian-nuclear-norm regularisation method. Specifically, the proposed method can achieve better and more balanced results in terms of peak-signal-to-noise ratio, convergence rate and restoration quality.

• 出版日期2018-5
• 单位南京理工大学; 南京邮电大学