SAR image speckle suppression based on area division and non-local total variation

Abstract

The invention discloses a method for SAR image speckle suppression based on area division and non-local total variation, which mainly resolves the problem of prior art that inhomogeneous area is involved in the homogeneous area when area is being divided, and introduces the thought of non-local total variation therein. The achieving steps are (1) acquiring the area mark from the sketch drawing of the Primal Sketch sparse representation model by utilizing geometric structure block, and dividing the SAR image into homogeneous area and inhomogeneous area, (2)processing the inhomogeneous area by utilizing method of non-local total variation speckle suppression in combination with singularities, (3) processing the homogeneous area by utilizing self-adaptive window Lee filtering method, (4) combining the speckle suppressed inhomogeneous area with the speckle suppressed homogeneous area to obtain the result of SAR image speckle suppression. The invention accomplishes the balance between singularity keeping and speckle suppression in SAR image speckle noise suppression and enhances the effect of SAR image speckle suppression.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to a SAR image coherent spot suppression method, and can be used for preprocessing of SAR image understanding and interpretation. Background technique [0002] Synthetic Aperture Radar (SAR) can work around the clock to obtain high-resolution images. Since it is a coherent imaging system, the images it produces must be polluted by coherent spots. In order to understand and interpret SAR images more effectively, it is necessary to perform speckle suppression preprocessing on SAR images. Local statistical adaptive filtering can effectively preserve the edge while smoothing the noise, and can adjust the smoothing effect and edge preservation effect through parameter control. It is one of the most commonly used speckle suppression methods. Most local statistical adaptive filtering methods are based on the assumption of fully developed coherent speckle, but the assumption of fully de...

AI Technical Summary

Problems solved by technology

However, the use of local statistical information to divide the image does not take into account the global structural information of the image, which will lead to inhomogeneity in a large uniform area and affect the effect of coherent speckle suppression in SAR images

[0003] The total variation model based on image restoration was originally proposed by Rudin, Osher and Fatemi. The advantage of this model over other models is that its solution space is a variogram space, and the functions in this space allow the existence of discontinuities such as edges. information, so the model can keep the edge of the image very well, but it also has two obvious disadvantages: one is easy to produce "staircase effect", and the other is that it does not maintain detailed information such as image texture.

However, the non-local total variation model is based on pixels, which does not take into account the local aggregation of the image, and cannot effectively improve the step effect of the image.

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