High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range
of exposures, which is important in image processing, computer graphics, and computer …

This paper reviews the first challenge on high-dynamic range (HDR) imaging that was part
of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in …

High Dynamic Range (HDR) images can be recovered from several Low Dynamic Range
(LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the …

Due to the poor lighting condition and limited dynamic range of digital imaging devices, the
recorded images are often under-/over-exposed and with low contrast. Most of previous …

The goal of high dynamic range (HDR) imaging is to estimate potential high-quality images
from multi-exposed low dynamic range (LDR) inputs. Intuitively, there exist various possible …

When one captures images in low-light conditions, the images often suffer from low visibility.
Besides degrading the visual aesthetics of images, this poor quality may also significantly …

High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …

Ghosting artifacts caused by moving objects or misalignments is a key challenge in high
dynamic range (HDR) imaging for dynamic scenes. Previous methods first register the input …

Standard digital cameras typically take images with under/overexposed regions because of
their sensors' limited dynamic range. The most common way to capture high dynamic range …

Image and video enhancement such as color constancy, low light enhancement, and tone
map** on smartphones is challenging because high-quality images should be achieved …