Sensors of different wavelengths in remote sensing field capture data. Each and every sensor has its own capabilities and limitations. Synthetic aperture radar (SAR) collects data that has a high spatial and radiometric resolution. The optical remote sensors capture images with good spectral information. Fused images from these sensors will have high information when implemented with a better algorithm resulting in the proper collection of data to predict weather forecasting, soil exploration, and crop classification. This work encompasses a fusion of optical and radar data of Sentinel series satellites using a deep learning-based convolutional neural network (CNN). The three-fold work of the image fusion approach is performed in CNN as layered architecture covering the image transform in the convolutional layer, followed by the activity level measurement in the max pooling layer. Finally, the decision-making is performed in the fully connected layer. The objective of the work is to show that the proposed deep learning-based CNN fusion approach overcomes some of the difficulties in the traditional image fusion approaches. To show the performance of the CNN-based image fusion, a good number of image quality assessment metrics are analyzed. The consequences demonstrate that the integration of spatial and spectral information is numerically evident in the output image and has high robustness. Finally, the objective assessment results outperform the state-of-the-art fusion methodologies.
Optical data taken in Jan. 97 from Silla compared to the discovery
plate of 1975.2 show no proper motion for PSR 08,33-45. while a
very significant one was expected if thc pulsar originated in the center of the Vela SNR, so far associaled with it. The data yield a good eslimate of the position of the parent SN event, highly asymmetric with respect lo the present SNR and incompatible with all the Vela ‘centers’ considered so far at various wavelengths. If the PSR/SNR association is lo be kept, either an extreme asymmetry of the SNR is required, or both objects are much older than so far thought. Both altematives appear not easy, thus possibly casting doubts on the reality of this classic SNR/pulsar association.