CAJ | 학술논문

为快速且准确地重建原始图像，提出一种新的图像复原算法。在稀疏表示的框架下，建立图像复原问题的约束优化模型，同步估计原始图像及其稀疏表示。复原模型的目标函数包含L1-L 2双正则项，为此采用交替优化将模型分解为若干子问题，交替迭代求解这些子问题。其中不可微分的子问题，由迭代重加权方法进行处理。实验结果表明，仅需较少次迭代该算法即可获得原始图像及其稀疏表示的最优估计。与某些优秀的同类算法相比，该算法的速度更快，复原图像的质量更高。
위쾌속차준학지중건원시도상，제출일충신적도상복원산법。재희소표시적광가하，건립도상복원문제적약속우화모형，동보고계원시도상급기희소표시。복원모형적목표함수포함L1-L 2쌍정칙항，위차채용교체우화장모형분해위약간자문제，교체질대구해저사자문제。기중불가미분적자문제，유질대중가권방법진행처리。실험결과표명，부수교소차질대해산법즉가획득원시도상급기희소표시적최우고계。여모사우수적동류산법상비，해산법적속도경쾌，복원도상적질량경고。
For rapidly and accurately restoring images, a novel image restoration algorithm is presented. In the framework of sparse representation, a new constrained optimization model is created, which enables the estimations of the original image and its sparse representation. The objective function of the model has L1-L2 regularized terms, thus the alternating optimization method is introduced to decompose the model into equivalent sub-problems. The non-differentiable one among sub-problems is handled by iterative reweighted method. The experimental results demonstrate that with only a few itera-tions, the presented algorithm can achieve optimal estimations of the original image and its sparse representation. Com-pared with some state-of-the-art algorithms, the presented algorithm shows to be faster, and obtains better results.