基于生成式深度图像先验结构的航空和合成孔径雷达图像恢复与增强

IF 2.1 4区 地球科学 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY PFG-Journal of Photogrammetry Remote Sensing and Geoinformation Science Pub Date : 2022-11-14 DOI:10.1007/s41064-022-00226-8
Architha Shastry, A. Smitha, S. George, P. Jidesh
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Restoration and Enhancement of Aerial and Synthetic Aperture Radar Images Using Generative Deep Image Prior Architecture
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来源期刊
CiteScore
8.20
自引率
2.40%
发文量
38
期刊介绍: PFG is an international scholarly journal covering the progress and application of photogrammetric methods, remote sensing technology and the interconnected field of geoinformation science. It places special editorial emphasis on the communication of new methodologies in data acquisition and new approaches to optimized processing and interpretation of all types of data which were acquired by photogrammetric methods, remote sensing, image processing and the computer-aided interpretation of such data in general. The journal hence addresses both researchers and students of these disciplines at academic institutions and universities as well as the downstream users in both the private sector and public administration. Founded in 1926 under the former name Bildmessung und Luftbildwesen, PFG is worldwide the oldest journal on photogrammetry. It is the official journal of the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF).
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