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Night Photography Rendering (NPR) poses a significant challenge due to the extreme contrast between dark and illuminated areas in scenes, stemming from concurrent capture of severely dark regions alongside intense point light sources.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Furkan Kınlı

Stack-based high dynamic range (HDR) imaging is a technique for achieving a larger dynamic range in an image by combining several low dynamic range images acquired at different exposures. Minimizing the set of images to combine, while…

Computer Vision and Pattern Recognition · Computer Science 2018-06-21 Peter van Beek

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 introduced in the imaging process. In order to obtain high…

Image and Video Processing · Electrical Eng. & Systems 2021-06-22 Xiangyu Chen , Yihao Liu , Zhengwen Zhang , Yu Qiao , Chao Dong

In this lecture note, we describe high dynamic range (HDR) imaging systems; such systems are able to represent luminances of much larger brightness and, typically, also a larger range of colors than conventional standard dynamic range (SDR)…

Graphics · Computer Science 2017-12-01 Alessandro Artusi , Thomas Richter , Touradj Ebrahimi , Rafal K. Mantiuk

This paper presents a new framework for jointly enhancing the resolution and the dynamic range of an image, i.e., simultaneous super-resolution (SR) and high dynamic range imaging (HDRI), based on a convolutional neural network (CNN). From…

Image and Video Processing · Electrical Eng. & Systems 2019-05-06 Jae Woong Soh , Jae Sung Park , Nam Ik Cho

This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR) do not go beyond factor 4. Missing information can be…

Very high-resolution (VHR) remote sensing (RS) scene classification is a challenging task due to the higher inter-class similarity and intra-class variability problems. Recently, the existing deep learning (DL)-based methods have shown…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Chiranjibi Sitaula , Sumesh KC , Jagannath Aryal

There are shadow and highlight regions in a low dynamic range (LDR) image which is captured from a high dynamic range (HDR) scene. It is an ill-posed problem to restore the saturated regions of the LDR image. In this paper, the saturated…

Computer Vision and Pattern Recognition · Computer Science 2021-11-16 Chaobing Zheng , Zhengguo Li , Shiqian Wu

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

We introduce the AIM 2025 Real-World RAW Image Denoising Challenge, aiming to advance efficient and effective denoising techniques grounded in data synthesis. The competition is built upon a newly established evaluation benchmark featuring…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Feiran Li , Jiacheng Li , Marcos V. Conde , Beril Besbinar , Vlad Hosu , Daisuke Iso , Radu Timofte

In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI Flash Portrait. Despite significant advancements in deep learning for image restoration,…

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

High Dynamic Range (HDR) imaging is gaining increased attention due to its realistic content, for not only regular displays but also smartphones. Before sufficient HDR content is distributed, HDR visualization still relies mostly on…

Computer Vision and Pattern Recognition · Computer Science 2020-01-22 Subhayan Mukherjee , Guan-Ming Su , Irene Cheng

This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal…

High Dynamic Range (HDR) content (i.e., images and videos) has a broad range of applications. However, capturing HDR content from real-world scenes is expensive and time-consuming. Therefore, the challenging task of reconstructing visually…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Hrishav Bakul Barua , Kalin Stefanov , KokSheik Wong , Abhinav Dhall , Ganesh Krishnasamy

Due to limited camera capacities, digital images usually have a narrower dynamic illumination range than real-world scene radiance. To resolve this problem, High Dynamic Range (HDR) reconstruction is proposed to recover the dynamic range to…

Image and Video Processing · Electrical Eng. & Systems 2023-12-14 Jiaqi Tang , Xiaogang Xu , Sixing Hu , Ying-Cong Chen

Deep high dynamic range (HDR) imaging as an image translation issue has achieved great performance without explicit optical flow alignment. However, challenges remain over content association ambiguities especially caused by saturation and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Hui Li , Xuyang Yao , Wuyuan Xie , Miaohui Wang

Accurately capturing dynamic scenes with wide-ranging motion and light intensity is crucial for many vision applications. However, acquiring high-speed high dynamic range (HDR) video is challenging because the camera's frame rate restricts…

Image and Video Processing · Electrical Eng. & Systems 2024-04-26 Caixin Wang , Jie Zhang , Matthew A. Wilson , Ralph Etienne-Cummings
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