Image restoration (IR) has been an indispensable and challenging task in the low-level
vision field, which strives to improve the subjective quality of images distorted by various …

We study the problem of multi-focus image fusion, where the key challenge is detecting the
focused regions accurately among multiple partially focused source images. Inspired by the …

Out-of-focus blur is a common image degradation phenomenon that occurs in case of lens
defocusing. The out-of-focus blur kernel is usually modeled as a Gaussian function or a …

Spiking neural networks (SNNs) have shown much promise as an energy-efficient
alternative to artificial neural networks (ANNs). Such methods trained by surrogate gradient …

In this paper, we propose a single image deblurring algorithm to remove spatially variant
defocus blur based on the estimated blur map. Firstly, we estimate the blur map from a …

Motivated by their great potential to reduce the size, cost, and weight, flat lenses, a category
that includes diffractive lenses and metalenses, are rapidly emerging as key components …

Face hallucination (FH) techniques have received a lot of attention in recent years for
generating high-resolution (HR) face images from captured low-resolution (LR), noisy, and …

The restoration of motion-blurred images has always been a complex problem in image
restoration. The current single blurred image algorithm cannot very well solve the estimation …

Blur detection and segmentation for a single image without any prior information is a
challenging task. Numerous techniques for blur detection and segmentation have been …

Nonlocal total variation (NLTV) has emerged as a useful tool in variational methods for
image recovery problems. In this paper, we extend the NLTV-based regularization to …