Diffusion models have achieved promising results in image restoration tasks, yet suffer from
time-consuming, excessive computational resource consumption, and unstable restoration …

High-fidelity information, such as 4K quality videos and photographs, is increasing as high-
speed internet access becomes more widespread and less expensive. Even though camera …

This work aims to improve the applicability of diffusion models in realistic image restoration.
Specifically, we enhance the diffusion model in several aspects such as network …

Efficient deep learning-based approaches have achieved remarkable performance in single
image super-resolution. However, recent studies on efficient super-resolution have mainly …

Clear and high-resolution (HR) underwater images are indispensable in acquiring
underwater information. However, existing underwater image enhancement and super …

The fusion between the low-resolution hyperspectral image (LRHSI) and the panchromatic
(PAN) image could obtain the high-resolution hyperspectral image (HRHSI). Recently, deep …

Blind super-resolution (BSR) methods based on high-resolution (HR) reconstruction
codebooks have achieved promising results in recent years. However, we find that a …

Though diffusion models have been successfully applied to various image restoration (IR)
tasks their performance is sensitive to the choice of training datasets. Typically diffusion …

High-resolution digital rock images are vital in studying microstructure and fluid flow
characterization of oil and gas reservoirs. Computed tomography (CT) is currently the …

Image Quality Assessment (IQA) is a challenging task that requires training on massive
datasets to achieve accurate predictions. However, due to the lack of IQA data, deep …