Weighted sum speckle reduction of multi-pass images

Sohner, Peter (1999). Weighted sum speckle reduction of multi-pass images B.Sc Thesis, School of Computer Science and Electrical Engineering, The University of Queensland.

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Author Sohner, Peter
Thesis Title Weighted sum speckle reduction of multi-pass images
School, Centre or Institute School of Computer Science and Electrical Engineering
Institution The University of Queensland
Publication date 1999-01-01
Thesis type B.Sc Thesis
Supervisor Dr. John Homer
Professor Dennis Longstaff
Total pages 54
Language eng
Subjects 0906 Electrical and Electronic Engineering
Formatted abstract

This thesis presents a weighted sum speckle reduction of multi-pass single-look synthetic aperture radar (SAR) images. Three different filtering techniques will be applied to both simulated and SAR image data. The methods used are Intensity Summation (IS), Weighted Intensity Summation (WIS), and Autoregressive (AR).

The mathematical matrix program called Matlab is used to apply these methods to the SAR images obtained by the ERS-1 satellite over Bonn in Germany. It is also used to simulate images and determine the optimal method of speckle reduction by measuring the equivalent number of looks (ENL).

The results showed that the AR method was optimal for the simulated images that had additive noise and the WIS method was optimal for the SAR images, which contained multiplicative noise.

It can be concluded that a high reduction of speckle can be achieved using multi-pass single-look images and by applying the WIS method to them. However, a combination of several techniques will produce the best speckle reduction.

Keyword Speckle reduction
Synthetic aperture radar (SAR)
Intensity summation (IS)
Weighted intensity summation (WIS)
Autoregressive (AR)
Additional Notes * 4th year electrical engineering theses and information technology abstracts. 1999

Document type: Thesis
Collection: UQ Theses (non-RHD) - UQ staff and students only
Citation counts: Google Scholar Search Google Scholar
Created: Wed, 29 May 2013, 22:38:06 EST by Mr Yun Xiao on behalf of Scholarly Communication and Digitisation Service