Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

In retinex model, images are considered as a combination of two components: illumination
and reflectance. However, decomposing an image into the illumination and reflectance is an …

Owing to imaging equipment's environment and limitations, the images obtained in industrial
cyber-physical systems (ICPSs) are degraded and available in various visual appearances …

This paper presents a novel approach for low-light image enhancement. We propose a deep
simultaneous estimation network (DSE-Net), which simultaneously estimates the reflectance …

In low-light image enhancement, single-exposure images contain a limited dynamic range,
which hinders the restoration of contrast and texture. To address these problems, we …

In the low light conditions, images are corrupted by low contrast and severe noise, but event
cameras capture event streams with clear edge structures. Therefore, we propose an Event …

This paper proposes a Fusion and Recalibration Network (FRN) for low-light image
enhancement. Firstly, The proposed method generates multi-exposure images from a single …

In this paper, we present a new approach for single image dehazing based on the proposed
variational optimization. A hazy image captures the information about haze in terms of the …

This paper proposes a Degradation-Aware Deep Retinex Network (DA-DRN) for enhancing
low-light images. DA-DRN is composed of a decomposition U-Net and an enhancement U …

Low-light conditions present a myriad of intricacies for object detection, with many existing
methods relying primarily on image enhancement before detection. Sometimes, the …