To process optical and SAR images, an image translation process-oriented Deep Adaptation-based Change Detection Technique (DACDT) is proposed. An optimized U-Net++ model is proposed that helps to improve the global and regional impacts of the images. Moreover, a multi-scale loss function is ...
Although feature-based methods have been successfully developed in the past decades for the registration of optical images, the registration of optical and synthetic aperture radar (SAR) images is still a challenging problem in remote sensing. In this letter, an improved version of the scale-invaria...
Aiming at improving the performance of scale invariant feature transform (SIFT) algorithm during the registration of optical and synthetic aperture radar (SAR) images, a new SIFT algorithm is proposed. Firstly, the nonlinear diffusion scale space of opti
In this article, we combined intensity- and feature-based similarity measures to co-register very-high-resolution (VHR) optical and SAR images. The global translation difference between optical and SAR images is minimized by applying a mutual information (MI) intensity-based similarity measure from ...
(a) and (b) are the optical and SAR images of the scene. (c) and (d) are the respective domain-specific goodness maps, after average pooling with Np=4 and Nk=1, (e) is the minimal response cross-modality goodness map G and (f) the final cross-modality scene goodness map Gˆ,...
This paper presents a method for denoising, feature extraction and compares classifications of Optical and SAR images. The image was denoised using K-Singular Value Decomposition (K-SVD) algorithm. A method to map the extraordinary goal signatures to be had withinside the SAR or Optical image ...
Moreover, the accuracy ofcity,village,road,water,forest, andfarmlandclassification was improved by 7%, 2%, 5%, 6%, 1%, and 0.6%, respectively, reflecting the superior performance of fusing optical and SAR images. Furthermore, the classification accuracy in Hubei Province of China, which covers ...
\\{SAR\\} and optical integrated data produced the best classification overall accuracies using both \\{MLC\\} and NN, respectively equal to 91.1% and 92.7% for \\{TM\\} and 95.6% and 97.5% for AVNIR-2. Texture information derived from optical images was critical, improving results ...
In order to model the related fault slip amplitude and geometry at depth, subpixel offsets tracking (here called correlograms) from Sentinel-2 optical and Sentinel-1 SAR images were calculated and used. Observations Post-seismic surface velocity map A post-seismic surface velocity map (Fig. 1c...
To solve the problems such as obvious speckle noise and serious spectral distortion when existing fusion methods are applied to the fusion of optical and SAR images, this paper proposes a fusion method for optical and SAR images based on Dense-UGAN and Gram–Schmidt transformation. Firstly, dense...