Image Inpainting Based on Geometrical Modeling of Complexwavelet Coefficients

The restoration of missing regions in images (inpainting) is mathematically an interpolation problem and has many important applications. This paper proposes a novel iterative inpainting algorithm based on the interpolation of the complex wavelet transform (CWT) coefficients with simple geometrical models on the magnitude and phase of the coefficients. The geometrical models describe the directionality and uniformity of the CWT magnitudes and the linearity of the CWT phases around edges and within texture areas. Both piecewise smooth signals and structured textures can be interpolated accurately with the proposed models. Motivated by the iterative reconstruction of an image from its CWT magnitude or phase, we propose an inpainting algorithm with iterative magnitude and phase estimation and CWT reconstruction. Simulation results show that the proposed algorithm achieves high PSNR and appealing visual quality with low computation complexity.