Abstract
Synthetic Aperture Radar (SAR) images inevitably contain speckle noise. Despeckling SAR images are typically represented as linear forms due to the consistency of denoising network training/inference settings on a linear scale. However, this leads to controversial problems when the linear SAR images are seen with the naked eye: i) restriction of representation for dark areas and ii) excessive expression for bright areas due to the high-intensity range. To overcome these problems, we propose a denoising framework that simultaneously eliminates speckle and thermal noise in the decibel (dB) domain through novel noise modeling. Our noise modeling allows the network to learn in the dB domain of the desired dynamic range, enabling stable end-to-end learning without separate spatial transformations. Our modeling is the first attempt to consider thermal noise. Experimental results show that our method is superior in quantitative and visual performance compared to the existing methods.
Original language | English |
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Title of host publication | AVSS 2022 - 18th IEEE International Conference on Advanced Video and Signal-Based Surveillance |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781665463829 |
DOIs | |
Publication status | Published - 2022 |
Event | 18th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2022 - Virtual, Online, Spain Duration: 2022 Nov 29 → 2022 Dec 2 |
Publication series
Name | AVSS 2022 - 18th IEEE International Conference on Advanced Video and Signal-Based Surveillance |
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Conference
Conference | 18th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2022 |
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Country/Territory | Spain |
City | Virtual, Online |
Period | 22/11/29 → 22/12/2 |
Bibliographical note
Funding Information:This work was supported by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2019-0-00079, Artificial Intelligence Graduate School Program(Korea University), No. B0101-15-0266, Development of High Performance Visual BigData Discovery Platform for Large-Scale Realtime Data Analysis).
Publisher Copyright:
© 2022 IEEE.
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Information Systems and Management
- Media Technology