A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
VLSI implementation of discrete wavelet transform
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Applied Wavelet Analysis with S-Plus
Applied Wavelet Analysis with S-Plus
IEEE Transactions on Signal Processing
A shift-invariant discrete wavelet transform
IEEE Transactions on Signal Processing
Image compression using wavelet transform and multiresolution decomposition
IEEE Transactions on Image Processing
Spatially adaptive wavelet-based multiscale image restoration
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
IEICE - Transactions on Information and Systems
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A modified two-dimensional (2-D) discrete periodized waelet transform (DPWT) based on the homeomorphic high-pass filter and the 2-D operator correlation algorithm is developed in this paper. The advantages of this modified 2-D DPWT are that it can reduce the multiplication counts and the complexity of boundary data processing in comparison to other conventional 2-D DPWT for perfect reconstruction. In addition, a parallel-pipeline architecture of the nonseparable computation algorithm is also proposed to implement this modified 2-D DPWT. This architecture has properties of noninterleaving input data, short bus width request, and short latency. The analysis of the finite precision performance shows that nearly half of the bit length can be saved by using this nonseparable computation algorithm. The operation of the boundary data processing is also described in detail. In the three-stage decomposition of an N x N image, the latency is found to be N2 + 2N + 18.