Subband Coding of Images Using the Singular Value Decomposition
TL;DRAbstract
The singular value decomposition method is proposed for the coding of the subband images generated via a two-dimensional (2-D) quadrature mirror filter analysis bank. This approach permits easy determination of the optimal bit allocation and by decomposing an image into singular vectors, a 2-D coding problem is transformed into a 1-D coding problem, for which a stable linear prediction algorithm exists. In addition, the determination of the SVD of subimages is much simpler than that of the original one, due to their considerably smaller sizes. Simulation results are presented to illustrate the performance characteristics of the proposed approach.
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The singular value decomposition method is proposed for the coding of the subband images generated via a two-dimensional (2-D) quadrature mirror filter analysis bank. This approach permits easy determination of the optimal bit allocation and by decomposing an image into singular vectors, a 2-D coding problem is transformed into a 1-D coding problem, for which a stable linear prediction algorithm exists. In addition, the determination of the SVD of subimages is much simpler than that of the original one, due to their considerably smaller sizes. Simulation results are presented to illustrate the performance characteristics of the proposed approach.
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