Paper
19 January 2006 Adaptive in-band motion compensated temporal filtering based on motion mismatch detection in the highpass subbands
Anyu Gao, Nishan Canagarajah, David Bull
Author Affiliations +
Proceedings Volume 6077, Visual Communications and Image Processing 2006; 60771F (2006) https://doi.org/10.1117/12.643110
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
This paper presents an adaptive in-band motion compensated temporal filtering (MCTF) scheme for 3-D wavelet based scalable video coding. The proposed scheme overcomes the problem of visual artifacts due to motion mismatch when motion information of the spatial lowpass subband is inaccurately applied to the highpass subbands in decoding high spatial resolution video. More specifically, the proposed scheme determines if the mismatch energy is beyond an acceptable threshold in the wavelet domain and then adaptively switches between using the motion information from the spatial lowpass and highpass subbands in the MCTF prediction step. As a result, the amount of motion overhead needs to be transmitted is minimized and a good trade-off between motion information and texture is realized. Experimental results show that the proposed scheme greatly improves the quality of the decoded video at high spatial resolutions while achieving a high coding efficiency. Furthermore, the proposed adaptive scheme requires only modifications when performing MCTF in the highpass subbands, hence the original strength of in-band MCTF for decoding low spatial resolution video is well preserved.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anyu Gao, Nishan Canagarajah, and David Bull "Adaptive in-band motion compensated temporal filtering based on motion mismatch detection in the highpass subbands", Proc. SPIE 6077, Visual Communications and Image Processing 2006, 60771F (19 January 2006); https://doi.org/10.1117/12.643110
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Cited by 2 scholarly publications.
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KEYWORDS
Video

Wavelets

Motion estimation

Visualization

Discrete wavelet transforms

Spatial resolution

Digital filtering

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