Pixel level fusion techniques for SAR and optical images: A review
SC Kulkarni, PP Rege - Information Fusion, 2020 - Elsevier
Image Fusion is a process of combining two or more images into a single image which is
more informative and hence more useful from an interpretation point of view. With the rapid …
more informative and hence more useful from an interpretation point of view. With the rapid …
From single-to multi-modal remote sensing imagery interpretation: A survey and taxonomy
Modality is a source or form of information. Through various modal information, humans can
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
More diverse means better: Multimodal deep learning meets remote-sensing imagery classification
Classification and identification of the materials lying over or beneath the earth's surface
have long been a fundamental but challenging research topic in geoscience and remote …
have long been a fundamental but challenging research topic in geoscience and remote …
Representation-enhanced status replay network for multisource remote-sensing image classification
Deep-learning-based methods are widely used in multisource remote-sensing image
classification, and the improvement in their performance confirms the effectiveness of deep …
classification, and the improvement in their performance confirms the effectiveness of deep …
Cloud-gan: Cloud removal for sentinel-2 imagery using a cyclic consistent generative adversarial networks
P Singh, N Komodakis - IGARSS 2018-2018 IEEE International …, 2018 - ieeexplore.ieee.org
Cloud cover is a serious impediment in land surface analysis from Remote Sensing images
either causing complete obstruction (thick clouds) with loss of information or blurry effects …
either causing complete obstruction (thick clouds) with loss of information or blurry effects …
Forest change detection in incomplete satellite images with deep neural networks
Land cover change monitoring is an important task from the perspective of regional resource
monitoring, disaster management, land development, and environmental planning. In this …
monitoring, disaster management, land development, and environmental planning. In this …
Cloud removal in remote sensing images using nonnegative matrix factorization and error correction
In the imaging process of optical remote sensing platforms, clouds are an inevitable barrier
to the effective observation of sensors. To recover the original information covered by the …
to the effective observation of sensors. To recover the original information covered by the …
Cloud removal with fusion of high resolution optical and SAR images using generative adversarial networks
The existence of clouds is one of the main factors that contributes to missing information in
optical remote sensing images, restricting their further applications for Earth observation, so …
optical remote sensing images, restricting their further applications for Earth observation, so …
SAR-to-optical image translation using supervised cycle-consistent adversarial networks
Optical remote sensing (RS) data suffer from the limitation of bad weather and cloud
contamination, whereas synthetic aperture radar (SAR) can work under all weather …
contamination, whereas synthetic aperture radar (SAR) can work under all weather …
A conditional generative adversarial network to fuse SAR and multispectral optical data for cloud removal from Sentinel-2 images
In this paper, we present the first conditional generative adversarial network (cGAN)
architecture that is specifically designed to fuse synthetic aperture radar (SAR) and optical …
architecture that is specifically designed to fuse synthetic aperture radar (SAR) and optical …