High dynamic range

About: High dynamic range is a research topic. Over the lifetime, 4280 publications have been published within this topic receiving 76293 citations. The topic is also known as: HDR.

Physical Validation of Global Illumination Methods: Measurement and Error Analysis

Abstract: In this paper, we present a physical validation of global illumination algorithms based on measurements from a simple experimental setup. The validation methodology emphasizes tractability and error minimization. To this end, we discuss issues such as the acquisition and accurate simulation of material bidirectional reflection distribution functions (BRDFs) and the light source distribution, as well as error analysis. In addition, we present a nearest-neighbor resampling technique for BRDFs and a simple method for extracting the light source distribution from digitized high dynamic range (HDR) images. Finally, we compare the measurements to a forward and backward raytracing solution (photon map and RADIANCE, respectively) in a set of case studies.

Motion aware exposure bracketing for HDR video

Abstract: Mobile phones and tablets are rapidly gaining significance as omnipresent image and video capture devices. In this context we present an algorithm that allows such devices to capture high dynamic range HDR video. The design of the algorithm was informed by a perceptual study that assesses the relative importance of motion and dynamic range. We found that ghosting artefacts are more visually disturbing than a reduction in dynamic range, even if a comparable number of pixels is affected by each. We incorporated these findings into a real-time, adaptive metering algorithm that seamlessly adjusts its settings to take exposures that will lead to minimal visual artefacts after recombination into an HDR sequence. It is uniquely suitable for real-time selection of exposure settings. Finally, we present an off-line HDR reconstruction algorithm that is matched to the adaptive nature of our real-time metering approach.

Weighted Least Squares Based Detail Enhanced Exposure Fusion

Abstract: Many recent computational photography techniques play a significant role to avoid limitation of standard digital cameras to handle wide dynamic range of the real-world scenes, containing brightly and poorly illuminated areas. In many of these techniques, it is often desirable to fuse details from images captured at different exposure settings, while avoiding visual artifacts. In this paper we propose a novel technique for exposure fusion in which Weighted Least Squares (WLS) optimization framework is utilized for weight map refinement. Computationally simple texture features (i.e., detail layer extracted with the help of edge preserving filter) and color saturation measure are preferred for quickly generating weight maps to control the contribution from an input set of multiexposure images. Instead of employing intermediate High Dynamic Range (HDR) reconstruction and tone mapping steps, well-exposed fused image is generated for displaying on conventional display devices. A further advantage of the present technique is that it is well suited for multifocus image fusion. Simulation results are compared with a number of existing single resolution and multiresolution techniques to show the benefits of the proposed scheme for variety of cases.

Rate-distortion optimized compression of high dynamic range videos

Abstract: An efficient algorithm to compress high dynamic range (HDR) videos is proposed in this work. We employ the motion information to separate an HDR video sequence into a tone-mapped low dynamic range (LDR) sequence and a ratio sequence. Then, those two sequences are encoded using the standard H.264/AVC codec. During the encoding, we allocate the limited bit budget to the LDR sequence and the ratio sequence optimally to maximize the qualities of the LDR and HDR sequences. Conventional LDR devices use only the LDR stream, whereas HDR devices reconstruct the HDR video using the LDR stream and the ratio stream. Simulation results show that the proposed algorithm provides better performance than the conventional methods.