arXiv · 1802.10291
FFT Multichannel Interpolation and Application to Image Super-resolution
Abstract
This paper presents an innovative set of tools to support a methodology for the multichannel interpolation (MCI) of a discrete signal. It is shown that a bandlimited signal $f$ can be exactly reconstructed from finite samples of $g_k$ ($1\leq k\leq M$) which are the responses of $M$ linear systems with input $f$. The proposed interpolation can also be applied to approximate non-bandlimited signals. Quantitative error is analyzed to ensure its effectiveness in approximating non-bandlimited signals and its Hilbert transform. Based on the FFT technique, a fast algorithm which brings high computational efficiency and reliability for MCI is presented. The standout performance of MCI is illustrated by several simulations. Additionally, the proposed interpolation is applied to the single image super-resolution (SISR). Its superior performance in accuracy and speed of SISR is demonstrated by the experimental studies. Our results are compared qualitatively and quantitatively with the state-of-the-art methods in image upsampling and reconstruction by using the standard measurement criteria.
Explore related subjects
Keep this discovery
Dong Cheng, Kit Ian Kou. 2018-02-28. FFT Multichannel Interpolation and Application to Image Super-resolution. https://doi.org/10.1016/j.sigpro.2019.03.025
Cite the original work for its findings. Save a collection to share your selection of sources.