A local structure adaptive super-resolution reconstruction method based on BTV regularization

作者：Zhou Lu; Lu Xiaobo^*; Yang Li

来源：Multimedia Tools and Applications, 2014, 71(3): 1879-1892.

DOI：10.1007/s11042-012-1311-x

• Super-resolution
• Bilateral Total Variation
• Local structure
• Regularization

Super-resolution (SR) image reconstruction has been one of the hottest research fields in recent years. The main idea of SR is to utilize complementary information from a set of low resolution (LR) images of the same scene to reconstruct a high-resolution image with more details. Under the framework of the regularization based SR, this paper presents a local structure adaptive BTV regularization based super-resolution reconstruction method to overcome the shortcoming of the Bilateral Total Variation (BTV) super resolution reconstruction model. The proposed method adaptively chooses prior model and regularization parameter according to the local structures. Experimental results show that the proposed method can get better reconstruction results and significantly reduces the manual workload of the regularization parameter selection.

• 出版日期2014-8
• 单位东南大学