An improved speckle reduction method of SAR image

被引：0

作者：

Zhang, Jianguo ^{[1
]}

Wang, Wenbo ^{[2
,3
]}

机构：

[1] Department of Foundation Course, Military Economic Academy, Wuhan

[2] College of Science, Wuhan University of Science and Technology, Wuhan

[3] The State Key Laboratory of Remote Sensing Science, Beijing

来源：

International Journal of Advancements in Computing Technology | 2012年 / 4卷 / 19期

关键词：

Empirical mode decomposition; Principle composition analysis; Speckle noise; Synthesis aperture radar (SAR) image;

D O I：

10.4156/ijact.vol4.issue19.69

中图分类号：

学科分类号：

摘要：

The speckle noise blurs the structure character of SAR image. It is difficult that to enhance structure character of SAR images. In this paper, a new approach is proposed to separate noise and source signals from SAR images. Firstly, the empirical mode function (EMD) is used to decompose the SAR image and a series basis components intrinsic mode function (IMF) are obtained. At the second stage, ICA is applied to denoise of IMFs and dominant basis components. In this method, the speckle noise of SAR image in different scale is filtered. The proposed method can effectively filter the speckle noise and enhance the structure character which finally can be seen by people's eyes. The experiment result indicates that speckle noise of our result is substantially decreased and the structure character and texture of the result is clearer.

引用

页码：579 / 585

页数：6

共 21 条

[1]

Kuttikkad S., Chellappa R., Statistical modeling and analysis of high-resolution synthetic aperture radar images, Stat. Comput, 10, pp. 13-145, (2000)

[2]

Goodman J.W., Some fundamental properties of speckle, J. Opt. Soc. Amer, 66, pp. 1145-1196, (1150)

[3]

Lee J.S., Refined filtering of image noise using local statistics, Comput. Grah. Image Process, 15, pp. 30-89, (1991)

[4]

Frost V.S., Stiles J.A., Shanumugan K.S., Holtzman J.C., A model for radar images and its application to adaptive digital filtering of multiplicative noise, IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-4, 2, (1986)

[5]

Jain A.K., Fundamentals of Digital Image Processing, (1999)

[6]

Donoho D.L., Denoising by softhresholding, IEEE Trans. Inf. Theory, 41, 3, pp. 613-627, (1995)

[7]

Vidakovic B., Statistical Modeling by Wavelets, (1999)

[8]

Zeng Z., Cumming I., Bayesian speckle noise reduction using the discrete wavelet transform, pp. 7-9, (1999)

[9]

Tsakalides A.P., Bezarianos A., SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling, IEEE Trans. Geosci. Remote Sens, 41, pp. 1773-1784, (2003)

[10]

Liu G., Ding X., Chen Q., Estimating spatiotemporal ground deformation with improved permanent-scatterer radar interferometry, IEEE Transactions on Geoscience and Remote sensing, 47, 8, pp. 2762-2772, (2009)

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