Image Inpainting Using Sparsity of the Transform Domain

Understand

In this paper, we propose a new image inpainting method based on the property that much of the image information in the transform domain is sparse.

• We add a redundancy to the original image by mapping the transform coefficients with small amplitudes to zero and the resultant sparsity pattern is used as the side information in the recovery stage.
• If the side information is not available, the receiver has to estimate the sparsity pattern.
• At the end, the recovery is done by consecutive projecting between two spatial and transform sets.