Real-world single image super-resolution: A brief review
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …
image from a low-resolution (LR) observation, has been an active research topic in the area …
A regularization by denoising super-resolution method based on genetic algorithms
Increasing the resolution of an image is an actual and extensively studied problem in image
processing. Recently, Regularization by Denoising (RED) showing that any inverse problem …
processing. Recently, Regularization by Denoising (RED) showing that any inverse problem …
An improved bilevel optimization approach for image super-resolution based on a fractional diffusion tensor
Variational regularization techniques are widely used to improve the quality of the super-
resolved image. However, the success of these methods depends on some sensitive …
resolved image. However, the success of these methods depends on some sensitive …
[HTML][HTML] A Single-Frame and Multi-Frame Cascaded Image Super-Resolution Method
The objective of image super-resolution is to reconstruct a high-resolution (HR) image with
the prior knowledge from one or several low-resolution (LR) images. However, in the real …
the prior knowledge from one or several low-resolution (LR) images. However, in the real …
Study of Deep Learning-based models for Single Image Super-Resolution.
The super-resolution of images has seen remarkable progress, especially with the use of
deep learning models. This technique allows having a better-quality image from one or more …
deep learning models. This technique allows having a better-quality image from one or more …
A novel image denoising approach based on a non-convex constrained PDE: application to ultrasound images
In this paper, we are interested in the mathematical and simulation study of a new non-
convex constrained PDE to remove the mixture of Gaussian–impulse noise densities. The …
convex constrained PDE to remove the mixture of Gaussian–impulse noise densities. The …
TARN: a lightweight two-branch adaptive residual network for image super-resolution
S Huang, J Wang, Y Yang, W Wan - International Journal of Machine …, 2024 - Springer
Currently, single-image super-resolution (SISR) methods based on convolutional neural
networks have achieved remarkable results. However, most methods improve the …
networks have achieved remarkable results. However, most methods improve the …
A new learning space-variant anisotropic constrained-PDE for image denoising
In this paper, we propose an improved enhancement space-variant anisotropic PDE-
constrained for image denoising, based on a learning optimization procedure. Since the …
constrained for image denoising, based on a learning optimization procedure. Since the …
[PDF][PDF] A Hybrid Regularization-Based Multi-Frame Super-Resolution Using Bayesian Framework.
The prime purpose for the image reconstruction of a multi-frame superresolution is to
reconstruct a higher-resolution image through incorporating the knowledge obtained from a …
reconstruct a higher-resolution image through incorporating the knowledge obtained from a …
[HTML][HTML] A multi-frame super-resolution based on new variational data fidelity term
The main idea of multi-frame super-resolution (SR) algorithm is to recover a single high-
resolution (HR) image from a sequence of low resolution ones of the same scene. Since the …
resolution (HR) image from a sequence of low resolution ones of the same scene. Since the …