In image denoising, deep convolutional neural networks (CNNs) can obtain favorable
performance on removing spatially invariant noise. However, many of these networks cannot …

We propose an infrared and visible fusion imaging method with a double-layer fusion
denoising neural network (DFDNN). The DFDNN is designed in an encoder-fusion-decoder …

With the increasing availability of devices that support ultra-high-definition (UHD) images,
Single Image Super Resolution (SISR) has emerged as a crucial problem in the field of …

In recent years, convolutional neural networks have obtained significant success in super-
resolution (SR) with remarkable performance. However, as the depth of the network …

Image restoration (IR) involves the retrieval of missing or damaged image information and
represents a significant challenge in the field of visual reconstruction. Currently, U-Net …

Transformers and Convolutional Neural Networks (CNN) have garnered significant attention
recently for low-level vision tasks, particularly image super-resolution (SR). However, CNNs …