CAJ | 학술논문

针对SAR图像超分辨重构问题,建立了基于多尺度Contourlet域的正则化模型.在选取正则化参数时,提出一种自适应确定方法,该方法无需知道噪声大小和图像的先验知识,提高了确定正则化参数的准确性;求解模型时用FR共轭梯度法来改善算法的收敛性.将该算法分别与空域中正则化算法和小渡域中正则化算法进行了比较,仿真实验结果表明,该算法较好地再现了各种边缘信息,其重构结果均优于其他两种方法.
침대SAR도상초분변중구문제,건립료기우다척도Contourlet역적정칙화모형.재선취정칙화삼수시,제출일충자괄응학정방법,해방법무수지도조성대소화도상적선험지식,제고료학정정칙화삼수적준학성;구해모형시용FR공액제도법래개선산법적수렴성.장해산법분별여공역중정칙화산법화소도역중정칙화산법진행료비교,방진실험결과표명,해산법교호지재현료각충변연신식,기중구결과균우우기타량충방법.
Aiming at the reconstruction of SAR image super-resolution,a regularization model based on multi-scale contourlet-domain is established.When choosing the regularization parameter,an adaptive method is proposed which needn't the noise and prior informa-tion of image,and enhances the veracity of the regularization parameter.The algorithm's convergence is improved by FR conjugate gradient method.Compared with, regularization algorithm in spatial domain and wavelet domain,computer simulations show that the pro-posed approach in this paper can properly retrieve the main information of original image and is superior to the other two methods.