Related Experiment Video
Updated: Jun 23, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
Published on: February 12, 2014
[Adaptive super resolution algorithm for under-sampled images]
Jie Peng1, Qi-fei Xu, Qing-wen Lv
1School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Objective:
A new algorithm of adaptive super-resolution (SR) reconstruction based on the regularization parameter is proposed to reconstruct a high-resolution (HR) image from the low-resolution (LR) image sequence, which takes into full account the inaccurate estimates of motion error, point spread function (PSF) and the additive Gaussian noise in the LR image sequence. We established a novel nonlinear adaptive regularization function and analyzed experimentally its convexity to obtain the adaptive step size. This novel algorithm can effectively improve the spatial resolution of the image and the rate of convergence, which is verified by the experiment on optical images.
Related Concept Videos
Upsampling
Super-resolution Fluorescence Microscopy
Downsampling
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Aliasing
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Sampling Theorem
