SAR-to-optical image translationgenerative adversarial networkscross-fusion reasoning structurewavelet decompositionSynthetic aperture radar (SAR) images have been extensively used in earthquake monitoring, resource survey, agricultural forecasting, etc. However, it is a challenge to interpret SAR images with...
synthetic aperture radar (SAR); target recognition; SAR-to-optical image translation; deep learning; conditional generative adversarial network (cGAN) Graphical Abstract1. Introduction Target recognition in synthetic aperture radar (SAR) imagery is widely used in civil and military scenarios because SAR ...
The high-resolution optical and synthetic aperture radar (SAR) images are widely used in many remote sensing application areas such as image fusion and change detection where image registration is a ...
By using these descriptors, the similarity of SAR and optical image patches can be calculated. This similarity metric is then used in a sliding window approach to identify the matching points in the optical reference image. Subsequently, the derived points can be utilized for co-registration of ...
Automatic optical-to-SAR image registration is considered as a challenging problem because of the inconsistency of radiometric and geometric properties. Feature-based methods have proven to be effective; however, common features are difficult to extract and match, and the robustness of those methods st...
Image registration is the basis for joint utilization of multisource scene information. However, accurate automatic registration of multisource remote sensing images remains a challenging task, especially for optical and synthetic aperture radar (SAR) images. Due to the large geometric and intensity diff...
Deep-learning-based image translation based on high-resolution synthetic aperture radar (SAR) images is investigated as a method of restoring cloud-occlusion areas in optical satellite images. To train SAR and optical images, a Fast Fourier Convolution block was added to the unpaired image-to-...
SAR-to-Optical Image Translation and Cloud Removal Based on Conditional Generative Adversarial Networks: Literature Survey, Taxonomy, Evaluation Indicators, Limits and Future DirectionsGENERATIVE adversarial networksSYNTHETIC aperture radarOPTICAL images
Optical images are rich in spectral information, but difficult to acquire under all-weather conditions, while SAR images can overcome adverse meteorological conditions, but geometric distortion and speckle noise will reduce the quality of SAR images and thus make image interpretation more challenging. Th...
Water and land classes derived from each algorithm – are used as input data, and then the required parameters for the fuzzy clustering of SENTINEL-1A SAR image, were calculated. Lake Constance, Germany has been chosen as the study area. In this study, additionally an interface plugin has ...