The direction-adaptive discrete wavelet transform (DADWT) proves to be a very competitive alternative in scalable wavelet-based compression of images, yielding impressive compression performance gains in comparison to the classical DWT. A major limitation of DADWT though stems from its complexity, requiring an exhaustive search for the optimum prediction direction to be employed in the directional lifting process. This paper proposes a novel algorithm to lower the complexity of the DADWT by predicting the optimal prediction direction using a gradient-based technique. The algorithm is developed based on a mathematical model of the prediction errors generated via directional lifting of an input wedge image. The proposed approach avoids a time-consuming exhaustive search and yet the prediction step remains very simple and fast. It is shown that the proposed algorithm brings a complexity-reduction factor of 11/4 for almost no penalty in the prediction accuracy.
Stevens, R, Munteanu, A, Cornelis, J & Schelkens, P 2008, Optimized Directional Lifting with Reduced Complexity. in EURASIP European Signal Processing Conference, EUSIPCO 2008, Lausanne, Switzerland. Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet, Stockholm, Sweden, 21/09/09.
Stevens, R., Munteanu, A., Cornelis, J., & Schelkens, P. (2008). Optimized Directional Lifting with Reduced Complexity. In EURASIP European Signal Processing Conference, EUSIPCO 2008, Lausanne, Switzerland
@inproceedings{1c0396a346c94f748d26e2dcebd87077,
title = "Optimized Directional Lifting with Reduced Complexity",
abstract = "The direction-adaptive discrete wavelet transform (DADWT) proves to be a very competitive alternative in scalable wavelet-based compression of images, yielding impressive compression performance gains in comparison to the classical DWT. A major limitation of DADWT though stems from its complexity, requiring an exhaustive search for the optimum prediction direction to be employed in the directional lifting process. This paper proposes a novel algorithm to lower the complexity of the DADWT by predicting the optimal prediction direction using a gradient-based technique. The algorithm is developed based on a mathematical model of the prediction errors generated via directional lifting of an input wedge image. The proposed approach avoids a time-consuming exhaustive search and yet the prediction step remains very simple and fast. It is shown that the proposed algorithm brings a complexity-reduction factor of 11/4 for almost no penalty in the prediction accuracy.",
keywords = "wavelet transform, geometric wavelets, wavelet-based coding",
author = "Robin Stevens and Adrian Munteanu and Jan Cornelis and Peter Schelkens",
year = "2008",
month = aug,
day = "27",
language = "English",
booktitle = "EURASIP European Signal Processing Conference, EUSIPCO 2008, Lausanne, Switzerland",
note = "Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet ; Conference date: 21-09-2009 Through 25-09-2009",
}