A New Approach of Joint Noise and Blur Removal for Multiframe Super-Resolution Reconstruction
The reconstruction of a super-resolution (SR) image from multiple low-resolution (LR) frames has drawn a lot of research attention over the past years. The SR reconstruction is an inherent ill-posed minimization problem. Though regularization constraint may be accomplished to derive a single solution, to implement a traditional approach which the data fusing is processed at high-resolution (HR) grids may still be a great challenge due to complexity as well as high computing load. In this paper we introduce a new approach which both the blur and noise removal would be simultaneously carried out at the LR grids by taking pixelwise time average upon the available LR frames after registration. This approach is characterized by simplicity and real-time applicability, and the simulation results demonstrate that the compatible performance can be achieved.
super-resolution image reconstruction registration anisotropic diffusion pixelwise time average
Ho-Hsuan Chang Jin-Shing Shia
Department of communication engineering I-Shou University Kaohsiung, Taiwan Military education division National Kaohsiung Normal University Kaohsiung, Taiwan
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
1068-1072
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）