一种新的SAR图像斑点噪声自适应抑制方法

摘要

To effectively preserve synthetic aperture radar (SAR) image edges while filtering, an anisotropic diffusion denoising model based on Euler's elastic energy model is presented. First, a minimum-energy variation model is derived from the anisotropic diffusion model. To preserve the image details while filtering, the Euler' s elastic energy model is introduced. Then an adaptive step-size iteration scheme is proposed to improve the computational efficiency. The new algorithm using both simulated and real SAR images is validated. The experimental results show that the proposed method not only preserves image details effectively while filtering, but also improves the computational efficiency.%在合成孔径雷达(synthetic aperture radar,SAR)图像斑点噪声抑制处理中,为有效保护图像细节,提出欧拉弹性能量各向异性扩散去噪模型.该模型将各向异性扩散模型转化为最小能量变分模型,结合欧拉弹性能量模型的边界保护和增强能力,在抑制噪声的同时能更有效地保护和增强细节信息.同时为了提高计算效率,提出自适应变步长去噪算法.仿真和真实SAR图像的实验结果表明,该算法不仅在抑制噪声的同时能够很好地保护图像细节,而且有效减少了计算时间、提高了效率.