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CNN-Type Algorithms for H.264 Variable Block-Size Partitioning

Lauri Koskinen, Ari Paasio, Kari Halonen, CNN-Type Algorithms for H.264 Variable Block-Size Partitioning. SIGNAL PROCESSING: IMAGE COMMUNICATION 22, 797–808, 2007.

Abstract:

Due to power consumption restrictions, low-power H.264 encoders cannot take
advantage of the variable block sizes available in H.264 motion estimation.
This work presents two methods to determine a block-size partition without
an initial search. With both of these methods, computationally burdensome
Lagrange optimization is not required. The methods are derived from a
cellular nonlinear network (CNN) segmentation algorithm and, along with the
partition, indicate early termination of motion estimation and the skip
modes of H.264. Both methods achieve better rate-distortion performance
when compared to motion estimation with only 16  16 sized blocks.
The 16 x 16 only case is descriptive of a low-power case where the variable
block sizes cannot be used. For low bitrates, both methods achieve
equivalent performance when compared to Lagrange optimization. Also
presented are the computational complexity of the methods and the power
consumption when implemented with existing CNN hardware.

BibTeX entry:

@ARTICLE{jKoPaHa07a,
  title = {CNN-Type Algorithms for H.264 Variable Block-Size Partitioning},
  author = {Koskinen, Lauri and Paasio, Ari and Halonen, Kari},
  journal = {SIGNAL PROCESSING: IMAGE COMMUNICATION},
  volume = {22},
  pages = {797–808},
  year = {2007},
}

Belongs to TUCS Research Unit(s): Microelectronics

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