调和映射约束下的超分辨率图像重建

针对超分辨率图像重建过程中的正则化约束问题,本文提出采用p(x)调和映射进行正则化重建,根据超分辨率图像观察模型及正则约束,给出相应的能量泛函,并采用动态偏微分方程演化来求解能量泛函.该算法在重建的过程中能够根据图像空间特性自适应地采用不同的p(x)范数进行正则化,在图像的平滑区域采用近似2次范数进行正则化,而在图像的边缘区域采用近似1次范数进行正则化.实验结果均表明该算法不仅能有效地重建图像边缘,而且能有效地改善一次范教约束重建的分片常数效应.

Super-resolution Reconstruction Based on the Harmonic Mapping Constraint

To solve the ill-posed problem of the super-resolution image regularization reconstruction, an energy function based on p(x) harmonic mapping regularization and super-resolution image observed model was drawn. The super-resolution image was obtained by a dynamic partial differential equation. The algorithm could adopt the different norm adaptively during regularization reconstruction, which used near 2-norm in smooth region and near 1-norm in the image edge region. The experiments show the algorithm not only reconstructs the super-resolution image efficiently, but also improves the "blocky" effect while preserving the edges.