Variable Bit Rate Video
Coding
April 18, 2002
(Compressed Video over Networks: Chapter 9)
Topics
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Introduction
Variable rate compression of video
Delay constraints
Impact of transmission modes
Encoder rate constraints
Rate control algorithms
Conclusions
Introduction
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VBR/CBR
• Coding modes (no. of bits per frame)
• Transport modes (no. of bits that can be transmitted during certain
periods of time)
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Video quality (end-to-end), distortion
• Depends on decisions at encoder (if lossy and online)
• Depends on transport (loss, bandwidth, delay)
• Tolerance depends on application
Variable rate compression
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Variable rate nature of compressed video:
• Input video characteristics (scene changes, redundancy varies)
• Coding parameters (quantizers, motion compensation)
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Constant quality requires variable bits per frame
Offline encoding (two-pass approach for DVD)
Distortion measurement (MSE)
Variable rate compression
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Ways of creating variable rate video
• Quantizer selection (with each block/macroblock; complicates for
video since RD of future frames depend on motion vectors)
• Frame type selection (I, P, B; I frames may be placed at fixed
interval, eg. every 0.5 sec)
• Frame skipping (use more bits/frame but less frame/s; use
interpolation at receiver)
Delay constraints
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Prevent decoder buffer underflow
i 1 N d
i
C   R ,
k 1
k
k 1
k
i
Ri = no. of bits assigned to frame i
Ci = no. of bits recd. by decoder buffer during ith frame interval
Td = I corresponds to ith frame intervals having passed
Delay constraints
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We assumed no frame skipping, and const. frame rate
Encoding and decoding delay constant.
Delays not considered:
• Transmitter buffer delay tb
• Transmission channel delay ch
• tb+ ch should not violate decoder buffer underflow constraint
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Constraints vary on
• Pre-encoded video
• Live video
• Interactive video
Impact of transmission modes
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CBR vs VBR transmission
• Better video quality, shorter delay, increased call capacity
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QoS, best-effort model of networks
Constrained vs. unconstrained transmission
• Eg. Transmission rate subject to conditions (peak rate/sustainable rate in
QoS) or congestion control in TCP/IP within best-effort transmission
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Feedback vs No Feedback
• Encoders can modulate data(quality/resolution/rate) based on feedback
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Modes of operation: U-VBR / U-SVBR/ C-VBR / F-VBR
Encoder Rate constraints
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Derive rate constraints that encoder/transmitter must meet
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Avoid violating delay constraints
Use channel information
Consider type of application (PEV/LIV/LNIV)
Memory restrictions (PDA)
Encoder Rate constraints
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To prevent decoder buffer underflow, encoder must avoid the
encoder buffer size exceeding
• CBR transmission mode
Beff  N d  C
• VBR with known channel rate
Beff (i) 
i  N
C
j i 1
j
• VBR with unpredictable channel rates
i  N 
Be (i)  E   C j 
 j i 1 
i  N

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P  Be (i)   C j   threshold
j i 1


Encoder Rate constraints
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Video caching
• Proxy caching of web objects
• Efficient sharing of resources
• Reduce initial latency
• Less likelihood of packet losses
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Replicate entire sequence
store prefix (for td seconds)
Store intermediate samples so that decoder does not starve
Coarse layers cached
Rate control algorithms
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Constraints placed so as to guarantee that decoder always has
data to decode
Video encoder should produce bitstream that meets these
constraints
To accomplish this, we need rate control algorithms
H.263, MPEG-2 do not define operation of encoder, so free to
use any rate control techniques
Rate control algorithms
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Problem formulation
• Rate constraints for set of frames, not of individual frame
• Decision on how to allocate bits among the set, so that the average
distortion is minimized – RD optimization
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CBR algorithms
• Each coding parameter is associated with a rate and distortion pair.
Find coding parameters within a finite set (for each frame) such that
distortion is lowest
• First calculate RD at all points and then optimize
• Gets complicated when dependency exists among frames
• Allow change of frame rate (find optimum, no jerky motion,
redundancy decreases among frames at low frame rate)
Rate control algorithms
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VBR algorithms
• Many parameters (rate, delay, etc.)
• Algorithms monitor the long-term average transmission rate and
keep it close to a value
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Real-time adaptation to channel conditions
• Encoder should react to channel changes (channel memory is long,
channel feedback is fast)
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Layered/Scalable video
• Incorporated in MPEG-2 standard, high complexity.
Conclusions
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VBR coding is the natural representation of video
Constraints need to be placed at encoder for best
quality
Transmission medium and service plays a critical role
Optimization algorithms used to find ideal rate at
encoder
Rate control gets even more challenging with
wireless mediums