Motion-compensated lifted wavelets have received much interest for video compression.
While they are biorthogonal, they may substantially deviate from orthonormality due to
motion compensation, even if based on an orthogonal or near-orthogonal wavelet.
A temporal transform for video sequences that maintains orthonormality while permitting
flexible motion compensation would be very desirable.
We have recently introduced such a transform for unidirectional motion compensation
from one previous frame [1].
See also sample video
[avi]
comparing to the motion-compensated lifted Haar wavelet.
In [3], we extend the idea to half-pel accurate motion compensation.
Orthonormality is maintained for arbitrary half-pel motion compensation by cascading
a sequence of incremental orthogonal transforms.
The half-pel intensity values are obtained by averaging neighboring integer-pel
positions.
Depending on the number of averaged integer-pel values, we use different types of
incremental transforms.
The cascade of incremental transforms allows us to choose in each step the optimal
type of incremental transform and, hence, the optimal half-pel position.
Half-pel motion-compensated blocks of arbitrary shape and size can be used as the
granularity of the cascade can be as small as one pixel.
The new half-pel accurate motion-compensated orthogonal video transform compares
favorably with the integer-pel accurate orthogonal transform.
In [4], we extend the idea to bidirectional motion compensation.
Orthonormality is maintained for arbitrary integer-pixel motion compensation by
cascading a sequence of incremental orthogonal 3x3 transforms. The energy of three
input pictures is accumulated in two temporal low-bands while the temporal high-band
is zero if the input pictures are identical after motion compensation.
Further, the motion-compensated orthogonal transforms can be cascaded to build a
dyadic wavelet decomposition.
The new bidirectionally motion-compensated orthogonal transform compares favorably
with the lifted 5/3 wavelet in video coding experiments with integer-pixel motion
compensation.
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[1]
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Markus Flierl and Bernd Girod:
A Motion-Compensated Orthogonal Transform with Energy-Concentration Constraint,
Proc. IEEE International Workshop on Multimedia Signal
Processing,
Victoria, BC, Oct. 2006.
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[2]
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Markus Flierl and Bernd Girod:
A Double Motion-Compensated Orthogonal Transform with Energy
Concentration Constraint,
Proc. SPIE Conference on Visual Communications and Image
Processing,
San Jose, CA, Jan. 2007.
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[3]
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Markus Flierl and Bernd Girod:
Half-Pel Accurate Motion-Compensated Orthogonal Video
Transforms,
Proc. IEEE Data Compression Conference,
Snowbird, UT, Mar. 2007.
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[4]
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Markus Flierl and Bernd Girod:
A New Bidirectionally Motion-Compensated Orthogonal Transform for
Video Coding,
Proc. IEEE International Conference on Acoustics, Speech, and
Signal Processing,
Honolulu, HI, Apr. 2007.
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[5]
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Markus Flierl and Bernd Girod:
Multiview Video Compression -- Exploiting Inter-Image
Similarities,
IEEE Signal Processing Magazine,
Special Issue on Multiview Imaging and 3DTV,
vol. 24, no. 6, pp. 66-76, Nov. 2007.
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[6]
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Markus Flierl:
Adaptive Spatial Wavelets for Motion-Compensated Orthogonal Video Transforms,
Proc. IEEE International Conference on Image Processing,
Cairo, Egypt, Nov. 2009.
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[7]
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Ousmane Barry, Du Liu, Stefan Richter, and Markus Flierl:
Robust Motion-Compensated Orthogonal Video Coding using EBCOT,
Proc. Pacific-Rim Symposium on Image and Video Technology,
Singapore, Nov. 2010.
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[8]
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Du Liu and Markus Flierl:
Video Coding with Adaptive Motion-Compensated Orthogonal
Transforms,
Proc. Picture Coding Symposium,
Krakow, Poland, May 2012.
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[9]
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Du Liu and Markus Flierl:
Fractional-Pel Accurate Motion-Adaptive Transforms,
IEEE Transactions on Image Processing,
vol. 28, no. 6, pp. 2731-2742, June 2019.
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