On the application of averaging median filters in remote sensing

1988 ◽  
Vol 26 (6) ◽  
pp. 832-838 ◽  
Author(s):  
A.A. Vassiliou ◽  
M. Boulianne ◽  
J.A.R. Blais
Keyword(s):  
Remote Sensing ◽  
Median Filters

scholarly journals An Efficient Adaptive Denoising Algorithm for Remote Sensing Images

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Xiujie Qu ◽  
Fu Zhang ◽  
Huan Jia
Keyword(s):  
Remote Sensing ◽  
Digital Images ◽  
Working Environment ◽  
Salt And Pepper Noise ◽  
Remote Sensing Images ◽  
Median Filters ◽  
Almost All ◽  
Salt And Pepper ◽  
Filter Algorithms ◽  
Adaptive Denoising

Typically, after the capturing, imaging, and transferring processes have been accomplished, the digital images will contain a variety of noise, caused by both the equipment itself and by the complex working environment. Consequently, it is necessary to perform a de-noising process to facilitate the extraction of useful information. This paper presents a fast and efficient denoising algorithm, which combines the advantages of traditional median filters and weighted filter algorithms. In this algorithm, the noise in the figure is determined, and those results are applied to adaptively change the size of the window, while assigning different weights to the pixels in the filter window. The experimental results show that we can significantly remove almost all salt and pepper noise, while retaining full image textures, edges, and other minutiae.

Phased Arrays for Radio Astronomy, Remote Sensing, and Satellite Communications

2018 ◽  
Author(s):  
Karl F. Warnick ◽  
Rob Maaskant ◽  
Marianna V. Ivashina ◽  
David B. Davidson ◽  
Brian D. Jeffs
Keyword(s):  
Remote Sensing ◽  
Radio Astronomy ◽  
Phased Arrays ◽  
Satellite Communications

Hyperspectral Imaging Remote Sensing

2016 ◽  
Author(s):  
Dimitris Manolakis ◽  
Ronald Lockwood ◽  
Thomas Cooley
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Imaging
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