Title :
Super-resolving compressed video with large artifacts
Author_Institution :
Sarnoff Corp., Princeton, NJ, USA
Abstract :
We propose methods to super-resolve compressed video sequences that may consist of frames with missing blocks of pixels in addition to compression artifacts. Different from traditional resolution enhancement algorithms, our methods include two key components that are crucial to handle compressed video sequences. The first component is dynamic masking that dynamically computes image masks used to reject outliers. The second component is flow-based image repairing that reconstructs missing blocks or a whole frame by exploring both temporal and spatial information. We demonstrate the proposed methods with real MPEG video sequences.
Keywords :
data compression; image enhancement; image reconstruction; image resolution; image sequences; video coding; MPEG video sequences; artifact compression; dynamic masking; flow based image repairing; image mask computing; image pixels; missing block reconstruction; resolution enhancement algorithms; spatial information; super-resolving compressed video sequences; temporal information; Bit rate; Focusing; Image coding; Image reconstruction; Image resolution; Signal resolution; Spatial resolution; Transform coding; Video compression; Video sequences;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334182