Title :
Spatiotemporal super-resolution for low bitrate H.264 video
Author :
Anantrasirichai, N. ; Canagar, C.N.
Author_Institution :
Univ. of Bristol, Bristol, UK
Abstract :
Super-resolution and frame interpolation enhance low resolution low-framerate videos. Such techniques are especially important for limited bandwidth communications. This paper proposes a novel technique to up-scale videos compressed with H.264 at low bit-rate both in spatial and temporal dimensions. A quantisation noise model is used in the super-resolution estimator, designed for low bitrate video, and a weighting map for decreasing inaccuracy of motion estimation are proposed. Results show improvement both in rate-distortion and perceived image quality.
Keywords :
data compression; image enhancement; image resolution; interpolation; motion estimation; quantisation (signal); video coding; frame interpolation enhancement; image quality; limited bandwidth communication; low bit rate H.264 video; low resolution low framerate video; motion estimation; quantisation noise model; spatiotemporal super resolution; super resolution estimator; video compression; Bit rate; Image coding; Noise; Quantization; Spatial resolution; Strontium; Interpolation; Video enhancement;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5651088