This paper describes a method for producing a sequence of higher resolution images from a sequence of low-resolution images containing sub-pixel shifts. This is possible in cases where aliasing is caused by the digitization process, and images of the low-resolution video sequence contain slightly different, but unique, information. The motion estimation is obtained by the respective group delays of local adaptive filters for optimal linear prediction. The main idea of the proposed iterative super resolution algorithm is that each high-resolution frame in the output sequence is generated from the previous high-resolution frame and a correction image. The correction image is the back projected filtered difference between the observed low-resolution image and the image obtained from the previous high-resolution frame using a simulation of the imaging system
Published in:
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
(Volume:1
)
Date of Conference: 16-20 Aug 1998