By Topic

A Combined Denoising Algorithm Approach to Sea Clutter in Wave Monitoring System by Marine Radar

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yanling Hao ; Coll. of Autom., Harbin Eng. Univ., Harbin ; Yanhong Tang ; Yi Zhu

X-band marine radar images are usually corrupted by noise due to random interference of electromagnetic waves. The noise degrades the quality of the images and makes interpretations and analysis of marine radar images harder. Therefore, noise reduction is necessary prior to the processing of marine radar images. In this paper a novel combined denoising algorithm approach to sea clutter in wave monitoring system by nautical radar is proposed. Firstly, the logarithmic transformation is used to convert the multiplicative noise model to an additive model. Secondly, the radar image is transformed with one-scale discrete wavelet transform (DWT). Thirdly, according to the noise characteristic the LL sub-band image is dealt with Wiener median filter, HL and LH sub-band images are dealt with mean filter, HH sub-band image is dealt with median filter. Finally, the wavelet inverse transformation and logarithmic inverse transformation are used to reconstruct the filtered image. The experimental results show that the proposed algorithm improves the denoising performance significantly.

Published in:

Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on  (Volume:3 )

Date of Conference:

20-22 Dec. 2008