摘要
超分辨率图像重建技术能够综合利用多帧离散图像、多组视频序列、或单帧图像与训练样本图像之间的互补信息,重建质量更好、空间分辨率更高的图像数据,弥补原有图像数据空间分辨率的不足,提高图像空间解像力和清晰度。介绍了基于正则化方法的超分辨率图像重建的研究现状和以正则化为基础的几种重建方法在近几年的研究和发展趋势。在此基础上,采用L1范数对重建图像保真度进行约束,利用总变分正则化克服重建问题的病态性,有效地保持了图像的边缘。实现了对包含文字信息的图像的正则化超分辨率重建,实验验证了方法的有效性。
Super resolution image reconstruction is a new technology which means to use multiple video sequences, or single - frame image and the training sample images of complementary information between the images to reconstruct a better quality, higher spatial resolution image data, make up the orig- inal image data is the lack of spatial resolution, improved image spatial resolution for force and clarity. Describes the method based on regularization of the super - resolution image reconstruction. On this basis, using the L1 norm of the reconstructed image fidelity constraint, the use of total variatJion regularization to overcome the ill - conditioned reconstruction problems, effectively maintain the edge of the image. To achieve a text message containing the image of regularized super - resolution reconstruction, experimental verification of the effectiveness of the method.
出处
《微处理机》
2012年第3期37-39,共3页
Microprocessors
关键词
总变分
正则化
超分辨率
L1范数
Total variation
Regularization
Super - resolution
L1 norm
