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Synthetic Aperture Radar (SAR) provides all-weather, high-resolution imaging capabilities, but its unique imaging mechanism often requires expert interpretation, limiting its widespread applicability. Translating SAR images into more easily…

计算机视觉与模式识别 · 计算机科学 2024-07-09 Xinyu Bai , Feng Xu

Synthetic Aperture Radar (SAR) provides robust all-weather imaging capabilities; however, translating SAR observations into photo-realistic optical images remains a fundamentally ill-posed problem. Current approaches are often hindered by…

计算机视觉与模式识别 · 计算机科学 2026-01-13 Hyunseo Lee , Sang Min Kim , Ho Kyung Shin , Taeheon Kim , Woo-Jeoung Nam

The utility of Synthetic Aperture Radar (SAR) imagery in remote sensing and satellite image analysis is well established, offering robustness under various weather and lighting conditions. However, SAR images, characterized by their unique…

计算机视觉与模式识别 · 计算机科学 2024-09-25 Grant Rosario , David Noever

Despite the advantages of all-weather and all-day high-resolution imaging, synthetic aperture radar (SAR) images are much less viewed and used by general people because human vision is not adapted to microwave scattering phenomenon.…

计算机视觉与模式识别 · 计算机科学 2019-10-10 Shilei Fu , Feng Xu , Ya-Qiu Jin

Synthetic Aperture Radar (SAR) offers all-weather, high-resolution imaging capabilities, but its complex imaging mechanism often poses challenges for interpretation. In response to these limitations, this paper introduces an innovative…

计算机视觉与模式识别 · 计算机科学 2024-07-25 Xinyu Bai , Feng Xu

Synthetic Aperture Radar (SAR) to electro-optical (EO) image translation is a fundamental task in remote sensing that can enrich the dataset by fusing information from different sources. Recently, many methods have been proposed to tackle…

计算机视觉与模式识别 · 计算机科学 2023-08-29 Jun Yu , Shenshen Du , Guochen Xie , Renjie Lu , Pengwei Li , Zhongpeng Cai , Keda Lu

Semantic segmentation for SAR (Synthetic Aperture Radar) images has attracted increasing attention in the remote sensing community recently, due to SAR's all-time and all-weather imaging capability. However, SAR images are generally more…

计算机视觉与模式识别 · 计算机科学 2022-10-18 Gao Mengyu , Dong Qiulei

In contrast to the well-investigated field of SAR-to-Optical translation, this study explores the lesser-investigated domain of Optical-to-SAR translation, a challenging field due to the ill-posed nature of this translation. The complexity…

计算机视觉与模式识别 · 计算机科学 2024-01-05 Moien Rangzan , Sara Attarchi , Richard Gloaguen , Seyed Kazem Alavipanah

Despite the advantages of all-weather and all-day high-resolution imaging, SAR remote sensing images are much less viewed and used by general people because human vision is not adapted to microwave scattering phenomenon. However, expert…

计算机视觉与模式识别 · 计算机科学 2019-01-15 Shilei Fu , Feng Xu , Ya-Qiu Jin

Synthetic Aperture Radar (SAR) imagery provides robust environmental and temporal coverage (e.g., during clouds, seasons, day-night cycles), yet its noise and unique structural patterns pose interpretation challenges, especially for…

计算机视觉与模式识别 · 计算机科学 2025-03-11 Jeonghyeok Do , Jaehyup Lee , Munchurl Kim

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…

计算机视觉与模式识别 · 计算机科学 2022-02-16 Xiaofan Qu , Feng Gao , Junyu Dong , Qian Du , Heng-Chao Li

Synthetic Aperture Radar (SAR) imagery has diverse applications in land and marine surveillance. Unlike electro-optical (EO) systems, these systems are not affected by weather conditions and can be used in the day and night times. With the…

计算机视觉与模式识别 · 计算机科学 2021-03-23 Abu Md Niamul Taufique , Navya Nagananda , Andreas Savakis

Earth observation satellites like Sentinel-1 (S1) and Sentinel-2 (S2) provide complementary remote sensing (RS) data, but S2 images are often unavailable due to cloud cover or data gaps. To address this, we propose a diffusion model…

计算机视觉与模式识别 · 计算机科学 2025-04-16 Kaan Aydin , Joelle Hanna , Damian Borth

Object detection and classification using aerial images is a challenging task as the information regarding targets are not abundant. Synthetic Aperture Radar(SAR) images can be used for Automatic Target Recognition(ATR) systems as it can…

计算机视觉与模式识别 · 计算机科学 2022-12-15 Sumanth Udupa , Aniruddh Sikdar , Suresh Sundaram

Driven by the complementary nature of optical and synthetic aperture radar (SAR) images, SAR-optical image matching has garnered significant interest. Most existing SAR-optical image matching methods aim to capture effective matching…

计算机视觉与模式识别 · 计算机科学 2025-08-12 Jingze Gai , Changchun Li

Existing deep learning-based methods can capture shared features from optical and synthetic aperture radar (SAR) images for spatial alignment. However, optical-SAR registration remains challenging under large geometric deformations, because…

计算机视觉与模式识别 · 计算机科学 2026-05-13 Zhuoyu Cai , Dou Quan , Ning Huyan , Pei He , Shuang Wang , Licheng Jiao

Image-to-image (I2I) translation is an established way of translating data from one domain to another but the usability of the translated images in the target domain when working with such dissimilar domains as the SAR/optical satellite…

计算机视觉与模式识别 · 计算机科学 2021-12-13 Alejandro D. Mousist

Synthetic Aperture Radar (SAR) imaging technology provides the unique advantage of being able to collect data regardless of weather conditions and time. However, SAR images exhibit complex backscatter patterns and speckle noise, which…

图像与视频处理 · 电气工程与系统科学 2025-04-22 Seon-Hoon Kim , Dae-Won Chung

There is rising interest in differentiable rendering, which allows explicitly modeling geometric priors and constraints in optimization pipelines using first-order methods such as backpropagation. Incorporating such domain knowledge can…

图像与视频处理 · 电气工程与系统科学 2023-08-09 Michael Wilmanski , Jonathan Tamir

Synthetic Aperture Radar (SAR) imagery provides all-weather, all-day, and high-resolution imaging capabilities but its unique imaging mechanism makes interpretation heavily reliant on expert knowledge, limiting interpretability, especially…

计算机视觉与模式识别 · 计算机科学 2025-03-26 Ruixi You , Hecheng Jia , Feng Xu
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