Deep Learning for HDR Imaging: State-of-the-Art and Future Trends

2021/10/20 by Lin Wang, Wang, Lin, Kuk‐Jin Yoon +1 · 4 citations
Computer Science · #Image Enhancement Techniques #Advanced Neural Network Applications #Image and Signal Denoising Methods

paper · pdf · doi:10.48550/arxiv.2110.10394

Abstract

High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision. In recent years, there has been a significant advancement in HDR imaging using deep learning (DL). This study conducts a comprehensive and insightful survey and analysis of recent developments in deep HDR imaging methodologies. We hierarchically and structurally group existing deep HDR imaging methods into five categories based on (1) number/domain of input exposures, (2) number of learning tasks, (3) novel sensor data, (4) novel learning strategies, and (5) applications. Importantly, we provide a constructive discussion on each category regarding its potential and challenges. Moreover, we review some crucial aspects of deep HDR imaging, such as datasets and evaluation metrics. Finally, we highlight some open problems and point out future research directions.

Citations

• Unsupervised Domain Adaptation with Residual Transfer Networks
• A Simple Framework for Contrastive Learning of Visual Representations

Cited by

• GMODiff: One-Step Gain Map Refinement with Diffusion Priors for HDR Reconstruction
• Real-time prediction of workplane illuminance distribution for daylight-linked controls using non-intrusive multimodal deep learning
• PhysHDR: When Lighting Meets Materials and Scene Geometry in HDR Reconstruction
• Capturing Stable HDR Videos Using a Dual-Camera System

Related

• HDR Image Reconstruction using an Unsupervised Fusion Model
• Deep Neural Networks for HDR imaging
• Deep Snapshot HDR Imaging Using Multi-Exposure Color Filter Array
• A Cycle Ride to HDR: Semantics Aware Self-Supervised Framework for Unpaired LDR-to-HDR Image Reconstruction
• Unsupervised HDR Imaging: What Can Be Learned from a Single 8-bit Video?