To further improve the translation results of SAR data, we propose a method of an adjacent dual-decoder UNet (ADD-UNet) based on conditional GAN (cGAN) for SAR-to-optical translation. The proposed network architecture adds an adjacent scale of the decoder to the UNet, and th...
SAR2EO: A High-resolution Image Translation Framework with Denoising Enhancement SAR2EO: A High-resolution Image Translation Framework with Denoising Enhancementdoi:10.48550/arXiv.2304.04760Synthetic Aperture Radar (SAR) to electro-optical ... J Yu,S Du,R Lu,... - 《Arxiv》 被引量: 0发表: ...
Synthetic aperture radar (SAR) and optical sensing are different earth observation methods. Compared to the optical sensors, the SAR has the imaging advantages such as all-weather, all-time, ability to traverse clouds and vegetation, etc. We propose the application of the cycle-consistent generativ...
The results provide the basis to explain fundamental limitations affecting the SAR-to-optical image translation idea but also indicate benefits from alternative SAR image representations. Keywords: synthetic aperture radar (SAR); deep learning; interpretation; generative adversarial networks Graphical Abstract...
Aiming at the above problems, Sar2color, an end-to-end general SAR-to-optical transformation model, is proposed based on a conditional generative adversarial network (CGAN). The model uses DCT residual block to reduce the effect of coherent speckle noise on the generated optical images, and ...
Source codes of "A Semi-Supervised Image-to-Image Translation Framework for SAR–Optical Image Matching" IEEE GRSL Prerequisites Python 3 Anaconda 3 NVIDIA GPU + CUDA cuDNN Getting Started Training python train.py --model semiD2 --dataroot "root of paired data" --dataroot_u "root of unpai...
In optical-to-SAR image registration, the SAR image is accurately aligned with the optical image. The latest satellites are providing the georeferenced remote sensing images which do not have any orientation and scaling differences [1]. The recent technologies are capable of producing the ...
Although image matching techniques have been developed in the last decades, automatic optical-to-synthetic aperture radar (SAR) image matching is still a challenging task due to significant nonlinear intensity differences between such images. This letter addresses this problem by proposing a novel simila...
SAR images contain abundant texture information, while optical images contain a wealth of contour information. Combining the advantages of both can result in images with richer information content. In this paper, we propose a CNN-based SAR image and optical image fusion model, named MSFusion, and...
An unsupervised optical-to-SAR translation framework named CDA-GAN is proposed to accomplish the high-quality training sample generation, by which the performance of target detection in the SAR domain can be improved; A cross-domain attention mechanism was designed to simultaneously emphasize discriminat...