强激光与粒子束, 2014, 26 (10): 101003, 网络出版: 2014-12-08  

自适应双树复小波遥感图像复原

Adaptive dual-tree complex wavelet algorithm for remote sensing image restoration
文奴 1,2,3,*杨世植 1,2崔生成 1,2程伟 1,2,3
作者单位
1 中国科学院 安徽光学精密机械研究所 光学遥感中心, 合肥 230031
2 中国科学院 通用光学定标与表征技术重点实验室, 合肥 230031
3 中国科学院大学, 北京 100049
摘要
由于遥感图像先验知识难以获取,提出了一种自适应的双树复小波迭代收缩复原算法。该算法根据模糊程度和噪声程度估计正则化参数,并利用经验公式计算收缩阈值。在实际应用中,算法能有效解决两步迭代算法使用固定参数的缺点,从而达到提高图像复原质量的目的。实验表明:相对于两步迭代算法,该算法复原图像的峰值信噪比提高0.64~12.23 dB,收敛速度提高1.4~16倍;同时,算法在提高图像复原质量、抑制噪声干扰及减少计算时间方面优势明显。
Abstract
An adaptive dual-tree complex wavelet algorithm was proposed to solve the classical image restoration problem. This method is more suited to the situation that a priori information of remote-sensing image is hard to obtain. The algorithm estimates regularization parameter from both the blurred level and the noise level, and estimates the noise using an empirical formula. In practical applications, the algorithm can effectively overcome the drawback of the two-step iterative shrinkage algorithm due to the use of a fixed parameter, and better imagery restoration quality could be obtained. Experimental results show that the image peak SNR improves 0.64-12.23 dB and the convergence speed improves 1.4-16 times. The algorithm has apparent advantages with respect of producing better restoration results, noise disturbance suppression and the reduction of computation time.

文奴, 杨世植, 崔生成, 程伟. 自适应双树复小波遥感图像复原[J]. 强激光与粒子束, 2014, 26(10): 101003. Wen Nu, Yang Shizhi, Cui Shengcheng, Cheng Wei. Adaptive dual-tree complex wavelet algorithm for remote sensing image restoration[J]. High Power Laser and Particle Beams, 2014, 26(10): 101003.

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