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Special Session 2: Spectral Image Processing

• Brief Description:
  Spectral image processing leverages the rich spectral information (from visible to infrared/ultraviolet bands) beyond traditional RGB images, enabling precise material identification, hidden feature extraction, and quantitative analysis. It has become a core technology in remote sensing, medical imaging, agricultural monitoring, industrial quality inspection, and environmental assessment. With the rapid advancement of hyperspectral/multispectral sensors and AI-driven algorithms, new challenges and opportunities emerge—such as balancing spectral-spatial resolution trade-offs, fully leveraging the characteristics of the spectral information, and adapting to real-world applications. To promote academic exchanges and technological innovation in this field, we hereby call for high-quality papers focusing on cutting-edge research and practical applications of spectral image processing.
  
  
  Session Organizers:
  Assoc. Prof. Lijuan Su, Beihang University, China
  Assoc. Prof. Xiaoming Ding, Tianjin Normal University, China
  
  
  The topics of interest include, but are not limited to:
  • Spatial Super-Resolution of Spectral Image
  • Spectral Super-Resolution of Spectral Image
  • Hyperspectral Image and Multispectral Image Fusion
  • Spectral Image Registration
  • Spectral Image Semantic Segmentation
  • Applications by using Spectral Image
  • Self-Supervised & Few-Shot Learning in Spectral Image Processing
  • Real-Time & Edge-Computing Solutions for Spectral Image Processing
  • Novel Datasets & Benchmarks for Spectral Image Processing
  
  
  Submission Method
  Submit your Full Paper (no less than 5 pages) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 2 (Spectral Image Processing)
  Template Download: (MS Word Template) (LaTeX Template)
  
  
  Introduction of Session Organizers
  
  

  
   

  Assoc. Prof. Lijuan Su
  Beihang University, China

   

   

   

  Lijuan Su is currently an associate professor of School of Instrumentation and Optoelectronic Engineering at BeiHang University. Received her BA degree of mechanical engineering from the University of Science and Technology of China in 2003, a MS degree of optical engineering from Chinese Academic of Science in 2006, and a PhD of industrial engineering from the Ohio State University in 2010. Prof Su’s research interests are mainly engaged in Optical Image Engineering and Image Processing technologies, specially focus on hyperspectral imaging techniques, light field imaging techniques as well as the hyperspectral image and light field image enhancement techniques.
  
  
  

  
   

  Assoc. Prof. Xiaoming Ding
  Tianjin Normal University, China

   

   

   

  Xiaoming Ding is currently a Associate Professor in the College of Electronic and Communication Engineering (College of Artificial Intelligence) at Tianjin Normal University, Tianjin, China. He obtained B.S. degree from the Opto-electronic Information Engineering at Beihang University in 2012. In 2019, he obtained Ph.D degree in Optical Engineering from Beihang University and joined Tianjin Normal University in the same year. He is a master's supervisor, and a member of the Tianjin Association for Artificial Intelligence. He has published over 30 papers in major academic journals and conferences. His main research areas include snapshot spectral imaging, computational imaging, spectral data processing, and deep learning, etc.