Dynamic Spatial Aggregation Network for Joint Denoising and HDR Imaging

Jun Xiao, Cuixin Yang, Cong Zhang, Yakun Ju, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Imaging systems often produce underexposed or overexposed images due to their limited capacity to capture the full range of natural illumination. To address this limitation, deep high dynamic range (HDR) imaging methods rely on fusing multiple low dynamic range (LDR) images, demonstrating remarkable performance in recent years. However, most existing methods solely focus on object motions, disregarding real-world noise in images, which typically leads to suboptimal solutions in actual situations. In this paper, we propose a dynamic spatial aggregation network, which can simultaneously handle noise and large motion of objects in LDR images in real-world scenarios. Our method employs a dynamic convolutional operator, which is image-specific and ensures robustness to noise and misaligned image content, to adaptively extract features from input LDR images. Experimental results demonstrate that our proposed method significantly outperforms state-of-the-art deep HDR models, resulting in high-quality HDR images in real-world situations.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Imaging Technology, IWAIT 2024
EditorsMasayuki Nakajima, Phooi Yee Lau, Jae-Gon Kim, Hiroyuki Kubo, Chuan-Yu Chang, Qian Kemao
ISBN (Electronic)9781510679924
Publication statusPublished - Jan 2024
Event2024 International Workshop on Advanced Imaging Technology, IWAIT 2024 - Langkawi, Malaysia
Duration: 7 Jan 20248 Jan 2024

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


Conference2024 International Workshop on Advanced Imaging Technology, IWAIT 2024


  • Computational Photography
  • High Dynamic Imaging
  • Image Processing

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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