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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 combined. In this paper we address the problem of predicting…

Computer Vision and Pattern Recognition · Computer Science 2017-11-28 Gabriel Eilertsen , Joel Kronander , Gyorgy Denes , Rafał K. Mantiuk , Jonas Unger

The research in dense online 3D mapping is mostly focused on the geometrical accuracy and spatial extent of the reconstructions. Their color appearance is often neglected, leading to inconsistent colors and noticeable artifacts. We rectify…

Computer Vision and Pattern Recognition · Computer Science 2018-04-23 Sergey V. Alexandrov , Johann Prankl , Michael Zillich , Markus Vincze

Ghosting artifacts, motion blur, and low fidelity in highlight are the main challenges in High Dynamic Range (HDR) imaging from multiple Low Dynamic Range (LDR) images. These issues come from using the medium-exposed image as the reference…

Image and Video Processing · Electrical Eng. & Systems 2022-11-07 Wei Li , Shuai Xiao , Tianhong Dai , Shanxin Yuan , Tao Wang , Cheng Li , Fenglong Song

Specular reflection exists widely in photography and causes the recorded color deviating from its true value, so fast and high quality highlight removal from a single nature image is of great importance. In spite of the progress in the past…

Computer Vision and Pattern Recognition · Computer Science 2015-12-02 Dongsheng An , Jinli Suo , Xiangyang Ji , Haoqian Wang , Qionghai Dai

We present High Dynamic Range Neural Radiance Fields (HDR-NeRF) to recover an HDR radiance field from a set of low dynamic range (LDR) views with different exposures. Using the HDR-NeRF, we are able to generate both novel HDR views and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Xin Huang , Qi Zhang , Ying Feng , Hongdong Li , Xuan Wang , Qing Wang

Despite significant advances in algorithms and hardware, global illumination continues to be a challenge in the real-time domain. Time constraints often force developers to either compromise on the quality of global illumination or…

Graphics · Computer Science 2024-06-13 Alexandr Kuznetsov , Stavros Diolatzis , Anton Sochenov , Anton Kaplanyan

We present a learning-based method to infer plausible high dynamic range (HDR), omnidirectional illumination given an unconstrained, low dynamic range (LDR) image from a mobile phone camera with a limited field of view (FOV). For training…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Chloe LeGendre , Wan-Chun Ma , Graham Fyffe , John Flynn , Laurent Charbonnel , Jay Busch , Paul Debevec

Recent innovations shows that blending of details captured by single Low Dynamic Range (LDR) sensor overcomes the limitations of standard digital cameras to capture details from high dynamic range scene. We present a method to produce…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Harbinder Singh , Dinesh Arora , Vinay Kumar

This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral camera arrays has gained importance in medical, agricultural,…

Image and Video Processing · Electrical Eng. & Systems 2024-11-14 Katja Kossira , Jürgen Seiler , André Kaup

The limited dynamic range of commercial compact camera sensors results in an inaccurate representation of scenes with varying illumination conditions, adversely affecting image quality and subsequently limiting the performance of underlying…

Computer Vision and Pattern Recognition · Computer Science 2022-05-17 Pranjay Shyam , Sandeep Singh Sengar , Kuk-Jin Yoon , Kyung-Soo Kim

Event cameras are ideally suited to capture High Dynamic Range (HDR) visual information without blur but provide poor imaging capability for static or slowly varying scenes. Conversely, conventional image sensors measure absolute intensity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Ziwei Wang , Yonhon Ng , Cedric Scheerlinck , Robert Mahony

In the real-life environments, due to the sudden appearance of windows, lights, and objects blocking the light source, the visual SLAM system can easily capture the low-contrast images caused by over-exposure or over-darkness. At this time,…

Robotics · Computer Science 2019-02-12 Yinghong Fang , Guangcun Shan , Xin Li , Wenliang Liu , Tian Wang , Hichem Snoussi

We develop a deep learning network to estimate the illumination spectrum of hyperspectral images under various lighting conditions. To this end, a dataset, IllumNet, was created. Images were captured using a Specim IQ camera under various…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Nariman Habili , Jeremy Oorloff , Lars Petersson

Due to hardware constraints, standard off-the-shelf digital cameras suffers from low dynamic range (LDR) and low frame per second (FPS) outputs. Previous works in high dynamic range (HDR) video reconstruction uses sequence of alternating…

Image and Video Processing · Electrical Eng. & Systems 2022-10-11 Zeeshan Khan , Parth Shettiwar , Mukul Khanna , Shanmuganathan Raman

While most images shared on the web and social media platforms are encoded in standard dynamic range (SDR), many displays now can accommodate high dynamic range (HDR) content. Additionally, modern cameras can capture images in an HDR format…

Image and Video Processing · Electrical Eng. & Systems 2025-03-18 Trevor D. Canham , SaiKiran Tedla , Michael J. Murdoch , Michael S. Brown

Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio parameter must be chosen manually to complete the enhancement…

Image and Video Processing · Electrical Eng. & Systems 2020-04-23 Qingxu Fu , Xiaoguang Di , Yu Zhang

Background The accuracy of photomechanics measurements critically relies on image quality,particularly under extreme illumination conditions such as welding arc monitoring and polished metallic surface analysis. High dynamic range (HDR)…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Banglei Guan , Jing Tao , Liang Xu , Dongcai Tan , Pengju Sun , Jianbing Liu , Yang Shang , Qifeng Yu

A single-pixel digital holography system with phase-encoded illumination using a digital micromirror device (DMD) as a spatial light modulator (SLM) is presented. The enhanced switching rate of DMDs, far exceeding the stringent frame-rate…

We advance the field of HDR environment map estimation from a single-view image by establishing a novel approach leveraging the Latent Diffusion Model (LDM) to produce high-quality environment maps that can plausibly light mirror-reflective…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Jack Hilliard , Adrian Hilton , Jean-Yves Guillemaut

Low dynamic range (LDR) cameras cannot deal with wide dynamic range inputs, frequently leading to local overexposure issues. We present a learning-based system to reduce these artifacts without resorting to complex acquisition mechanisms…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Yazhou Xing , Amrita Mazumdar , Anjul Patney , Chao Liu , Hongxu Yin , Qifeng Chen , Jan Kautz , Iuri Frosio
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