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Introduction
Published in Francesco Banterle, Alessandro Artusi, Kurt Debattista, Alan Chalmers, Advanced High Dynamic Range Imaging, 2017
Francesco Banterle, Alessandro Artusi, Kurt Debattista, Alan Chalmers
An HDR image may be generated by capturing multiple images of the same scene at different exposure levels and merging them to reconstruct the original dynamic range of the captured scene. There are several algorithms for merging LDR images; Debevec and Malik’s method [111] is an example of these. One commercial implementation is SpheronVR’s SpheronCam HDR [351] that can capture still spherical images with a dynamic range of 6 × 106 : 1. Although information could be recorded in one shot using native HDR CCDs, problems of low sensor noise typically occur at high resolution.
Sensors for Autonomous Vehicles in Infrastructure Inspection Applications
Published in Diego Galar, Uday Kumar, Dammika Seneviratne, Robots, Drones, UAVs and UGVs for Operation and Maintenance, 2020
Diego Galar, Uday Kumar, Dammika Seneviratne
Since cameras rely on ambient light, the quality of images can be greatly affected by the time of day and weather. High dynamic range (HDR) imaging can help with image quality caused by under- or over-lit conditions, glare, etc. HDR works by taking multiple photos with different light exposures and fusing the images together. This broadens the range of luminosity of a usable picture. This greater range of luminosity allows better images, which, in turn, can improve perception of the environment and strengthen fusion of LiDAR, radar, and camera data.
Digital Image Formats
Published in Cliff Wootton, A Practical Guide to Video and Audio Compression, 2005
Even worse are the hue-shifting effects that you get as a result of gamut clipping. Shooting directly into the sun shows up in the image as a darkened blotch in the area that is brightest. The rendered color is some strange hue that seems to bear no resemblance to the surrounding image. It is like a severe crushing effect on the peak value of the video. High-dynamic range imaging (HDR) allows a greater range of tones to be stored, and this leads to better quality video being created after it has been processed.
A Review of Illuminance Mapping Practices from HDR Images and Suggestions for Exterior Measurements
Published in LEUKOS, 2023
Arpan Guha, Alayne Nyboer, Dale K. Tiller
Thus, conventional photography techniques only allow differentiation within a certain, limited dynamic range; any features in the image outside this range appear to be lighter in the brighter areas of the image or darker in the darker areas while not accurately representing what the eye sees. This is overcome by employing High Dynamic Range (HDR) Imaging, a technique used to reproduce a greater range of light and color. An HDR image is created by combining multiple LDR images hence increasing the dynamic range of the resultant image and making it more photorealistic. Capturing a series of LDR images, taken from the lowest exposure setting to the highest exposure setting and combining them creates one single HDR image. The resultant HDR image contains a wide dynamic range of the scene therefore making the image photorealistic. A comparison between an LDR image and an HDR image is shown in Fig. 1.