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 …

Multi-exposure image fusion (MEF) is emerging as a research hotspot in the fields of image
processing and computer vision, which can integrate images with multiple exposure levels …

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 …

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 …

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 …

Synthesizing high dynamic range (HDR) images from multiple low-dynamic range (LDR)
exposures in dynamic scenes is challenging. There are two major problems caused by the …

This paper proposes the first non-flow-based deep framework for high dynamic range (HDR)
imaging of dynamic scenes with large-scale foreground motions. In state-of-the-art deep …

One of the most challenging problems in reconstructing a high dynamic range (HDR) image
from multiple low dynamic range (LDR) inputs is the ghosting artifacts caused by the object …

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

Abstract Mapping Low Dynamic Range (LDR) images with different exposures to High
Dynamic Range (HDR) remains nontrivial and challenging on dynamic scenes due to …