GRSS Special Stream on Efficient and Real-time Processing Methods for Remote Sensing Image Interpretation
Remote sensing technology has played a vital role in a wide range of Earth observation applications, including disaster monitoring, environmental protection, marine surveillance, and urban planning. Recent advancements in remote sensing satellite constellation construction and space information networks, along with the growing trend of deploying edge computing devices directly on remote sensing platforms, offer new opportunities for achieving efficient, real-time information perception and intelligent decision-making. However, most existing high-performance remote sensing data processing methods heavily rely on powerful computational resources due to their large number of parameters and complex model architectures. This reliance significantly hinders their deployment on resource-constrained edge devices, such as satellites and unmanned aerial vehicles (UAVs). Furthermore, traditional model lightweighting techniques often lead to noticeable performance degradation, limiting their practical effectiveness. Therefore, it is of critical importance to investigate novel approaches for efficient and real-time remote sensing data processing that can balance model complexity with performance, particularly for deployment in edge computing environments.
List of Topics
- Real-time processing architecture/system for remote sensing images
- Edge-cloud collaborative methods for remote sensing image interpretation
- Acceleration of foundation models in the domain of remote sensing
- Efficient algorithms for data preprocessing
- Efficient algorithms for target detection/recognition/segmentation/change detection
- Intelligent and rapid algorithms for data fusion of multi-sensor
- Pruning, quantization and compression methods for deep learning algorithms
- Parallel mapping strategy of embedded system for remote sensing
Guest Editors:
- Yue Zhang, Beijing University of Posts and Telecommunications, Beijing, China
- Biplab Banerjee, Indian Institute of Technology Bombay, India
- Yin Zhuang, Beijing Institute of Technology, Beijing, China
- Saurabh Prasad, University of Houston, Houston, TX, USA
Schedule:
- Submission System Open: May 14, 2025
- Submission System Close: August 31, 2025
All submissions must be formatted using the IEEE standard format (double-column, single-spaced) typically 4-5 pages. Please use the following link to download the article template. All submissions will be peer-reviewed according to the GRSS guidelines. Submitted articles should not have been published or be under review elsewhere. Submit your manuscript to ieee.atyponrex.com/journal/grsl , using the Author Portal interface, and select our specific stream.
