Mitigating decorrelation effects on interferometric synthetic aperture radar (InSAR) time
series data is challenging. The phase linking (PL) algorithm has been the key to handling …

Detection tasks based on Synthetic aperture radar (SAR) images have been studied widely
but severely constrained by the quality of datasets. Meanwhile, both the unperceived …

Probabilistic Diffusion Models (PDMs) have recently emerged as a very promising class of
generative models, achieving high performance in natural image generation. However, their …

成像雷达具有全天时, 全天候的观测能力, 能够通过成像处理获得目标雷达图像信息,
是对地观测, 侦察监视等民用和军用领域中的重要遥感设备. 高分辨率雷达图像能够提供目标的 …

In the domain of synthetic aperture radar (SAR) image processing, a prevalent issue persists
wherein research predominantly focuses on single-task learning, often neglecting the …

Generative Adversarial Networks (GANs) have shown tremendous potential in synthesizing
a large number of realistic SAR images by learning patterns in the data distribution. Some …

Object classification in synthetic aperture radar (SAR) imagery is a challenging task, due to
the low resolution and high-level speckle noise. The electro-optical (EO) images provide …

An excellent quantitative evaluation method of SAR de-speckling filters needs to contain a
comprehensive evaluation of both noise smoothing and edge preservation. However, most …

Radar possesses the capability for all-day, all-weather observation and can generate radar
target images through image processing. It serves as an indispensable piece of remote …

Embedding distribution alignment is an approach to transfer knowledge from label-abundant
electro-optical (EO) images to the label-scarce synthetic aperture radar (SAR) modality …