Shadiya N, Ameer Ali
Abstract: A tear results in local image data loss and a relative shift in the frame between the regions at either side of the tear boundary. This paper proposes algorithms for the digital restoration of images damaged by tear. It describes a method for delineating the tear boundary and for correcting the displacement. For a high-quality image restoration, a missing-data treatment algorithm is used to recover any missing pixel intensities. To construct a high resolution image of the restored image, an interpolation technique is also proposed in this paper. Image interpolation aims in reconstructing a high resolution (HR) image from one or more low resolution (LR) images. It is better to explore the linear relationship among neighboring pixels to reconstruct a high-resolution image from a low-resolution input image. This paper uses an efficient method to determine the local order of the linear model implicitly. According to this theory, a method for performing single image super resolution is proposed by formulating the reconstruction as the recovery of a low rank matrix, which can be solved by the augmented Lagrange multiplier method. In addition, the proposed method can be used to handle noisy data and random perturbations robustly.
Keywords: Augmented Lagrange Multiplier, Image Interpolation, Low rank matrix recovery, Super resolution