# Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network

arXiv: https://arxiv.org/abs/2104.06699 · HTML: https://mlsanity.com/paper/2104.06699/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 17 references that are in the map.
- First posted on arXiv 14 Apr 2021.

## Builds on (most cited first, 3 of 3)

- [Learning in the Frequency Domain](https://mlsanity.com/paper/2002.12416/) (2020)
- [Compressed Video Action Recognition](https://mlsanity.com/paper/1712.00636/) (2017)
- [GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection](https://mlsanity.com/paper/1905.01662/) (2019)

## Built on by (most cited first, 11 of 11)

- [Change Detection Methods for Remote Sensing in the Last Decade: A Comprehensive Review](https://mlsanity.com/paper/2305.05813/) (2023)
- [Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images](https://mlsanity.com/paper/2204.08454/) (2022)
- [TransY-Net:Learning Fully Transformer Networks for Change Detection of Remote Sensing Images](https://mlsanity.com/paper/2310.14214/) (2023)
- [The Change You Want To Detect: Semantic Change Detection In Earth Observation With Hybrid Data Generation](https://mlsanity.com/paper/2503.15683/) (2025)
- [Adaptive Frequency Enhancement Network for Remote Sensing Image Semantic Segmentation](https://mlsanity.com/paper/2504.02647/) (2025)
- [Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network](https://mlsanity.com/paper/2203.06543/) (2022)
- [Synthetic Aperture Radar Image Change Detection via Layer Attention-Based Noise-Tolerant Network](https://mlsanity.com/paper/2208.04481/) (2022)
- [Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection](https://mlsanity.com/paper/2309.12010/) (2023)
- [Wavelet-based Bi-dimensional Aggregation Network for SAR Image Change Detection](https://mlsanity.com/paper/2407.13151/) (2024)
- [SSN: Stockwell Scattering Network for SAR Image Change Detection](https://mlsanity.com/paper/2304.11404/) (2023)
- [Prototype-Based Information Compensation Network for Multi-Source Remote Sensing Data Classification](https://mlsanity.com/paper/2505.04003/) (2025)

## Abstract (arXiv)

Change detection from synthetic aperture radar (SAR) imagery is a critical yet challenging task. Existing methods mainly focus on feature extraction in spatial domain, and little attention has been paid to frequency domain. Furthermore, in patch-wise feature analysis, some noisy features in the marginal region may be introduced. To tackle the above two challenges, we propose a Dual-Domain Network. Specifically, we take features from the discrete cosine transform domain into consideration and the reshaped DCT coefficients are integrated into the proposed model as the frequency domain branch. Feature representations from both frequency and spatial domain are exploited to alleviate the speckle noise. In addition, we further propose a multi-region convolution module, which emphasizes the central region of each patch. The contextual information and central region features are modeled adaptively. The experimental results on three SAR datasets demonstrate the effectiveness of the proposed model. Our codes are available at https://github.com/summitgao/SAR_CD_DDNet.