Fractional-Order Multi-scale Variation PDE Model and Adaptive Algorithm for SAR Image Denoising

Zhang Jun; Wei Zhi-hui

doi:10.3724/SP.J.1146.2009.00894

Volume 32 Issue 7

Aug. 2010

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Zhang Jun, Wei Zhi-hui. Fractional-Order Multi-scale Variation PDE Model and Adaptive Algorithm for SAR Image Denoising[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1654-1659. doi: 10.3724/SP.J.1146.2009.00894

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Zhang Jun, Wei Zhi-hui. Fractional-Order Multi-scale Variation PDE Model and Adaptive Algorithm for SAR Image Denoising[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1654-1659. doi: 10.3724/SP.J.1146.2009.00894

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Fractional-Order Multi-scale Variation PDE Model and Adaptive Algorithm for SAR Image Denoising

doi: 10.3724/SP.J.1146.2009.00894

Received Date: 2009-06-19
Rev Recd Date: 2010-03-09
Publish Date: 2010-07-19

Abstract

Abstract

In the processing of Synthetic Aperture Radar (SAR) image speckle noise reduction, maintaining the edges and textures of image are very important. This paper proposes a fractional-order multi-scale Partial Differential Equation (PDE) model by modeling the image with fractional-order derivative and negative Sobolev space, and then gives the adaptive selection method for the model parameters and the region-scale adaptive algorithm for SAR image denoising. Numerical experiments show that the new method can achieve better results in removing the noise, restraining the staircase effect and preserving edges and textures.

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References

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