The impact of tree structures on the performance of zerotree-based wavelet video codecs

  • Authors:

  • Athar Ali Moinuddin;Ekram Khan;Mohammed Ghanbari

  • Affiliations:

  • Department of Electronics Engineering, Aligarh Muslim University, Aligarh, UP 202002, India;Department of Electronics Engineering, Aligarh Muslim University, Aligarh, UP 202002, India;School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK

  • Venue:
  • Image Communication
  • Year:
  • 2010

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Abstract

In this paper we analyze the impact of tree structures on the performance of zerotree-based wavelet video codecs. Since zerotree approach is based on aggregation of insignificant coefficients in trees, therefore design of a tree structure is the key issue for a better performance. We have considered six different tree structures with characteristics varying from a simple to relatively complex and composite tree structures to code the luminance-chrominance components of a video sequence. Their performances are compared in terms of average number of bits generated per bitplane, number of coded bitplanes for a given bit budget, rate-distortion performance, memory requirements and computational complexity. We observe that in general more complex and longer trees do not necessarily improve the coding efficiency. However, the tree structures encapsulating more elements per tree are memory efficient. Therefore, the rate-distortion performance, memory requirements and computational complexities need to be traded-off while selecting a particular tree structure. It is also observed that the additional improvement due to optional entropy coding is also tree structure dependent. Further, the simulation results show that by designing an efficient tree structure, depending on the picture content, the performance of a video coder can be improved by up to 2.0dB, while reducing the computational complexity by 45-60% as well as the memory requirements by almost 29-35%. Compared to the standard JPEG2000 (for intra-frame), tree-based coders are found to be efficient in terms of coding and complexity, particularly at lower bit rates.