Abstract
Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.
Highlights
Due to some unique characteristics of Synthetic Aperture Radar (SAR), such as all-weather, capability of penetrating cloud cover, and special reflect spectrum for object, this gives it a considerable advantage over other infrared or optical sensors
We compare the results of the proposed level set filter with those of six existing schemes, that is, Lee filter, Enhanced Lee Filter, Kuan Filter, Frost Filter, Enhanced Frost Filter, Gamma Filter
Based on degraded image, result images computed by traditional methods such as Lee filter, Enhanced Lee Filter, Kuan Filter, Frost Filter, Enhanced Frost Filter, Gamma Filter and proposed level set filter are denoted in Figures 2(c), 2(d), 2(e), 2(f), 2(g), 2(h), and 2(i), respectively
Summary
Due to some unique characteristics of Synthetic Aperture Radar (SAR), such as all-weather, capability of penetrating cloud cover, and special reflect spectrum for object, this gives it a considerable advantage over other infrared or optical sensors. In order to remove speckle and keep edge, an alternative approach is proposed in this paper, it mainly relies on the theory of curvature anisotropic flow, that is, level set method. After the analysis, the relationship between curvature flow and Lee speckle filter, we considered further and deduced the anisotropic diffusion filter into a formulation of level set. In order to avoid long-term iteration in the manner of traditional anisotropic diffusion, the different speed of flow approach was introduced into the new technique as a selective smoothing switch according to effects by intensity and curvature gradient of neighbor pixels.
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