A Review: Image Interpolation by Low-Rank Matrix and Bilinear Method

Abstract: Image interpolation occurs in all digital photos at some stage. It happens anytime you resize or remap your image. Many researchers are working on improving image resolutions with different algorithms. When a low-resolution image is down sampled from the corresponding high-resolution image without blurring, the reconstruction becomes an image interpolation problem. Hence, this is a way to define the linear relationship among side by pixels to reconstruct a high-resolution image from a low-resolution image. In low rank matrix completion and recovery, a process for performing single-image super resolution is initiated by formulating the reconstruction as the recovery of a low-rank matrix. Besides that this method can be utilized to process noisy data. In this paper, we have studied and reviewed different interpolation methods.

Keywords: super-resolution, Image interpolation, low-rank matrix recovery, reconstruction augmented Lagrange multiplier