Author:
Khosravi Mohammad R.,Samadi Sadegh
Abstract
AbstractNowadays, industrial video synthetic aperture radars (ViSARs) are widely used for aerial remote sensing and surveillance systems in smart cities. A main challenge of a group of networked ViSAR sensors in an IoT-based environment is low bandwidth of wireless links for communicating big video data. In this research, we propose a non-linear statistical estimator for adaptive reconstruction of compressed ViSAR data. Our proposed reconstruction filter is based on an adaptively generated non-linear weight mask of spatial observations. It can strongly outperform several conventional and well-known reconstruction filters for three different video samples.
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Computer Science Applications,Signal Processing
Reference31 articles.
1. J. Lua, M. Xiab, W. Li, An interpolation algorithm using center coordinates of pixels for converting SDTV images to HDTV images. Optik. 124, 5251–5253 (2013)
2. R. Dianat, M. Ghanbari, Comparison between various standard definition to high definition image conversion methods. Recent Advances in Communications and Networking Technology. 4, 6–15 (2015)
3. Gonzalez, R.C.; Woods, R.E. Digital image processing, 3rd edition, 2008, Prentice Hall, New Jersey.
4. Khosravi, M.R. et al. A new statistical technique for interpolation of landsat images. ICAUCAE 2016, SID Conference Publications, 2016.
5. A. Baghaie, Z. Yu, Structure tensor based image interpolation method. International Journal of Electronics and Communications. 69, 515–522 (2015)
Cited by
12 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献