CAJ | 학술논문

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。
유우요감도상선험지식난이획취,제출료일충자괄응적쌍수복소파질대수축복원산법。해산법근거모호정도화조성정도고계정칙화삼수,병이용경험공식계산수축역치。재실제응용중,산법능유효해결량보질대산법사용고정삼수적결점,종이체도제고도상복원질량적목적。실험표명：상대우량보질대산법,해산법복원도상적봉치신조비제고0.64~12.23 dB,수렴속도제고1.4~16배；동시,산법재제고도상복원질량、억제조성간우급감소계산시간방면우세명현。
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 es-timates regularization parameter from both the blurred level and the noise level,and estimates the noise using an empirical formu-la.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 im-age peak SNR improves 0.64-12.23 dB and the convergence speed improves 1.4-16 times.The a lgorithm has apparent advanta-ges with respect of producing better restoration results,noise disturbance suppression and the reduction of computation time.