Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its
inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of
removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as
depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle
and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and
the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which
is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the
complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost
function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution
of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the
real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method.
Further more, the proposed method can preserve the information about images phase.
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