Algorithm efficiency scales linearly.
The effect of this approach is investigated and shown to increase algorithm efficiency and stability.
This process, also regarded as a constrained sampling step, has significant impact on the algorithm efficiency.
Algorithm efficiency, robustness, breakdown point, limitations, advantages, etc. are compared and analysed.
Results showed that the algorithm efficiency is not dependent on these parameters.
The algorithm efficiency and convergence properties are demonstrated by simulation study.
Experimental results demonstrate that our method can ensure the quality of SR images and improve the algorithm efficiency.
Image quality and algorithm efficiency are the two core problems of super resolution (SR) from a single image.
In simulations of aerosol particle removal by dry deposition in atmospherically relevant conditions, we demonstrate about 50-times increase in algorithm efficiency.
Instead, we search and match patches in a localized region of the image in each level, which can improve the algorithm efficiency.
