An Anisotropic PDE for Multi-frame Super-Resolution Image Reconstruction

Mourabit, Idriss El; Hakim, Abdelilah; Laghrib, Amine

doi:10.1007/978-3-030-83442-5_3

Cited by 2 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This adaptive diffusion-based PDE can efficiently preserve image features but it suffers from the blurring effect. A more robust PDE was proposed by El Mourabit et al [13,14] which takes into consideration the coherence-enhancing property and avoids blur much better. However, when the blur and noise levels are too high, the obtained HR image still contains some artefacts, in particular the blur.…”

Section: Introductionmentioning

confidence: 99%

An improved PDE-constrained optimization fluid registration for image multi-frame super resolution

et al. 2022

Self Cite

View full text Add to dashboard Cite

The main idea of multi-frame super resolution (SR) algorithms is to recover a single high-resolution image from a sequence of low resolution ones of the same object. The success of the SR approaches is often related to a well registration and restoration steps. Therefore, we propose a new approach based on a partial differential equation (PDE)-constrained optimization fluid image registration and we use a fourth order PDE to treat both the registration and restoration steps that guarantee the success of SR algorithms. Since the registration step is usually a variational ill-posed model, a mathematical study is needed to check the existence of the solution to the regularized problem. Thus, we prove the existence and of the well posed fluid image registration and assure also the existence of the used second order PDE in the restoration step. The results show that the proposed method is competitive with the existing methods.

show abstract

Section: Introductionmentioning

confidence: 99%