基于正则化变分模型的SAR图像增强方法

SAR IMAGE ENHANCEMENT BASED ON REGULARIZATION VARIATION MODEL

讨论合成孔径雷达(SAR)图像的噪声抑制与分辨率增强问题.建立偏微分方程抑噪方法与正则化点增强方法相结合的正则化变分模型,该模型同时具有偏微分方程模型的抑噪优势和正则化模型的分辨率增强优势.在图像的背景区域采用偏微分方程模型进行噪声抑制,而在图像的目标区域,先采用后向扩散方程进行锐化,然后再采用正则化模型进行分辨率增强,使整幅图像的处理结果均得到优化.此外,在偏微分方程抑噪模型的构造上,结合SAR成像的工程背景,提出了基于SAR图像幅度信息的前向-后向扩散方程,使方程能有效抑制图像背景区域的噪声并锐化目标边缘.大量的试验结果表明该方法能有效增强目标的强散射点,显著抑制噪杂波区的噪声.

The problem of noise reducing and resolution enhancement of SARimage was discussed. A unified regularization variation model of partial differential equation （PDE） was established, which has the noise reducing merit of PDE model and the resolution enhancement merit of regularization model. On the background of the image, the PDE model was used to reduce the noise of background, and at the targets region of the image, a background equation was used to sharp the targets firstly, then the regularization model was used to enhance the resolution of the targets. Hence, the new model can get better result on the whole image. The diffusivity based on the background of SAR was also constructed, and a forward and backward diffusion equation based on the amplitude of SAR image was obtained, which could reduce the noise of background and sharp the edges of targets. Experimental results show thatthe new model can enhance the strong scatter points and suppress the speckle of the image effectively.