Camera sensors can only capture a limited range of luminance simultaneously, and in order
to create high dynamic range (HDR) images a set of different exposures are typically …

Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR)
input image is challenging due to missing details in under-/over-exposed regions caused by …

High dynamic range (HDR) imaging provides the capability of handling real world lighting as
opposed to the traditional low dynamic range (LDR) which struggles to accurately represent …

Most consumer-grade digital cameras can only capture a limited range of luminance in real-
world scenes due to sensor constraints. Besides, noise and quantization errors are often …

High dynamic range (HDR) images can record much more intensity levels than usual ones.
Existing methods mainly reconstruct HDR images from the 8-bit low dynamic range (LDR) …

High dynamic range (HDR) video reconstruction from sequences captured with alternating
exposures is a very challenging problem. Existing methods often align low dynamic range …

Recent advances in camera designs and imaging pipelines allow us to capture high-quality
images using smartphones. However, due to the small size and lens limitations of the …

Recently, high dynamic range (HDR) imaging has attracted much attention as a technology
to reflect human visual characteristics owing to the development of the display and camera …

Deep learning is commonly used to produce impressive results in reconstructing HDR
images from LDR images. LDR stack-based methods are used for single-image HDR …

The mismatch between the Low Dynamic Range (LDR) content and the High Dynamic
Range (HDR) display arouses the research on inverse tone map** algorithms. In this …