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 …
Image restoration for remote sensing: Overview and toolbox
Remote sensing provides valuable information about objects and areas from a distance in
either active (eg, radar and lidar) or passive (eg, multispectral and hyperspectral) modes …
either active (eg, radar and lidar) or passive (eg, multispectral and hyperspectral) modes …
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
SAR image despeckling using a convolutional neural network
Synthetic aperture radar (SAR) images are often contaminated by a multiplicative noise
known as speckle. Speckle makes the processing and interpretation of SAR images difficult …
known as speckle. Speckle makes the processing and interpretation of SAR images difficult …
SAR image despeckling through convolutional neural networks
In this paper we investigate the use of discriminative model learning through Convolutional
Neural Networks (CNNs) for SAR image despeckling. The network uses a residual learning …
Neural Networks (CNNs) for SAR image despeckling. The network uses a residual learning …
A tutorial on speckle reduction in synthetic aperture radar images
Speckle is a granular disturbance, usually modeled as a multiplicative noise, that affects
synthetic aperture radar (SAR) images, as well as all coherent images. Over the last three …
synthetic aperture radar (SAR) images, as well as all coherent images. Over the last three …
NL-SAR: A unified nonlocal framework for resolution-preserving (Pol)(In) SAR denoising
Speckle noise is an inherent problem in coherent imaging systems such as synthetic
aperture radar. It creates strong intensity fluctuations and hampers the analysis of images …
aperture radar. It creates strong intensity fluctuations and hampers the analysis of images …
A nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage
S Parrilli, M Poderico, CV Angelino… - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
We propose a novel despeckling algorithm for synthetic aperture radar (SAR) images based
on the concepts of nonlocal filtering and wavelet-domain shrinkage. It follows the structure of …
on the concepts of nonlocal filtering and wavelet-domain shrinkage. It follows the structure of …
Learning a dilated residual network for SAR image despeckling
In this paper, to break the limit of the traditional linear models for synthetic aperture radar
(SAR) image despeckling, we propose a novel deep learning approach by learning a non …
(SAR) image despeckling, we propose a novel deep learning approach by learning a non …
Nonlocal patch similarity based heterogeneous remote sensing change detection
Change detection of heterogeneous remote sensing images is an important and challenging
topic, which has found a wide range of applications in many fields, especially in the …
topic, which has found a wide range of applications in many fields, especially in the …