Skip to Main Content
An algorithm for video resolution enhancement is presented. The approach borrows from previous methods for still-image super- resolution, introducing modifications better suited for the characteristics specific to video domain problems. Each high-resolution (HR) frame is determined through a series of MMSE spatial interpolations based on the local features (statistics) of the frame. Cross-frame registration is estimated externally and the reconstruction algorithm does not limit the form of the motion model, unlike previous data-fusion/deconvolution approaches which have required motion models that do not alter the point-spread function (i.e., motion/blur commutability). This feature is made possible using a reverse motion model mapping the locations of desired HR pixels onto their corresponding locations in the observation frames. An ticipating the existence of registration error found in typical video sequences, the algorithm also provides an internal validation of the observation pixels, helping to reduce significant mis-registration artifacts. An arbitrary enhancement factor can be used, allowing an output at any desired resolution. Interpolation and deblurring are incorporated as a single MMSE filtering operation, providing a non-iterative one-step reconstruction process. Experimental results demonstrating the capabilities of the algorithm are made available.