Image nonlocal self-similarity (NSS) property has been widely exploited via various sparsity
models such as joint sparsity (JS) and group sparse coding (GSC). However, the existing …

We consider the reconstruction problem of video snapshot compressive imaging (SCI),
which captures high-speed videos using a low-speed 2D sensor (detector). The underlying …

Group sparse representation (GSR) has made great strides in image restoration producing
superior performance, realized through employing a powerful mechanism to integrate the …

As a spotlighted nonlocal image representation model, group sparse representation (GSR)
has demonstrated a great potential in diverse image restoration tasks. Most of the existing …

Recent works that utilized deep models have achieved superior results in various image
restoration (IR) applications. Such approach is typically supervised, which requires a corpus …

The 4K content can deliver a more immersive visual experience to consumers due to the
huge improvement in spatial resolution. However, the high spatial resolution brings a great …

Recently, Transformer-based image denoising methods have achieved great progress in the
image denoising task. However, these methods also lead to two problems:(a) Since noise …

Multi-focus image fusion plays an important role in the application of computer vision. In the
process of image fusion, there may be blurring and information loss, so it is our goal to …

Recent deep convolutional neural networks for real-world noisy image denoising have
shown a huge boost in performance by training a well-engineered network over external …

To address the ill-posed problem of hyperspectral image super-resolution (HSISR), a
commonly employed technique is to design a regularization term based on the prior …