Spatio-temporal video interpolation and denoising using motion-assisted steering kernel (MASK) regression

In this paper, we extend a (2-D) data-adaptive steering kernel regression framework for image processing to a (3-D) spatio-temporal framework for processing video. In particular, we propose a motionassisted steering kernel (MASK) suitable for interpolating video data spatially, temporally, or spatio-temporally, and for video noise reduction. We present an algorithm for multi-frame interpolation and reconstruction of video data, and present several simulation results on synthetic and real video data. Comparisons between single-frame and multi-frame kernel regression and with other methods demonstrate the effectiveness of our approach.

• Type: Conference
• Year: 2008
• Where: ICIP
• Authors: Hiroyuki Takeda, Peter van Beek, Peyman Milanfar
• Keywords: ICIP 2008, Image Processing, Kernel Regression, Steering Kernel, Video Data