Existing image inpainting algorithms based on neural network models are affected by
structural distortions and blurred textures on visible connectivity. As a result, overfitting and …

Inpainting is the ancient art technique of modifying the image when it can't be detected. This
current study discusses the various approaches in image inpainting and compares the …

As an important display mode of underwater environments, the sonar image has limitations
on the resolution, which often leads to problems with low resolution of underwater objects …

In a summer2winter image-to-image translation, trees should be transformed from green to
gray, but the colors of houses or girls should not be changed. However, current …

Face super-resolution (SR) is a process of restoring the high-resolution (HR) face images
from the low-resolution (LR) inputs. Recently, deep learning-based methods have shown …

Single-image superresolution (SISR) is one of the requisite image processing methods used
to reconstructs a high-resolution (HR) image from a low-resolution (LR) observation. Existing …

Sparse representation-based single image super-resolution (SISR) methods use a coupled
overcomplete dictionary trained from high-resolution images/image patches. Since remote …

Nowadays, single image super-resolution based on deep learning algorithms is reaching
state-of-the-art performance. Nevertheless, most frameworks suffer from needing huge …

Face image super-resolution imaging is an important technology which can be utilized in
crime scene investigations and public security. Modern CNN-based super-resolution …

Nowadays, the increasing demands for synthetic aperture radar images are of great
importance in both marine and terrestrial applications, due to their availability day and night …