In this paper, several VLSI architectures and implementations of Shape-Adaptive Discrete Wavelet Transform (SADWT) with odd symmetric biorthogonal filters are presented. The hardware implementation issues of SA-DWT algorithm are first addressed, and one lifting scheme together with some appropriate shape information processing units is introduced for the 1-D SA-DWT architectures. These architec...

We rst describe a multiresolutional discretization scheme for the boundary of a planar connected shape, by means of the Haar wavelet transform. This scheme yields a hierarchy of polygons of increasing complexity that adaptively captures the shape's boundary at increasing resolutions. Next, we present a new morphological transform called the Chordal Axis Transform for planar shapes that leads to...

A low complexity wavelet packet transform-based least mean square (LMS) adaptive beamformer is presented in this paper. This beamformer uses wavelet packet transform as the preprocessing, reduces the signal dimension in wavelet packet domain for low complexity and denoising, and employs least mean square algorithm to implement adaptive beamformer. Theoretical analysis and simulations demonstrat...

This paper proposes a new scheme for light field compression that incorporates disparity compensation into wavelet decomposition based on lifting. Disparity-compensated wavelet decomposition is firstly applied to exploit similarity between different views. The resulting coefficient images are encoded using shape-adaptive discrete wavelet transform followed by a modified SPIHT coder. The resulta...

Using wavelet transform to handle auto-mobile image with complex background for license localization, then preprocess license characters on vehicle licenses, and extracting the textural features of license characters in wavelet space, this paper proposed a novel algorithm for vehicle license localization and character recognition which is based on adaptive wavelet neural networks. Firstly, it u...

This paper studies the adaptive wavelet design for fabric defect detection. In order to achieve translation invariance and more flexible design, the wavelet design focused on nonsubsampled wavelet transform. We design the wavelet filters under the constraints that the analysis filters are power complementary, and the wavelet has only one vanishing moment, which corresponds to a multiscale edge ...

in analyzing a signal, especially a non-stationary signal, it is often necessarythe desired signal to be segmented into small epochs. segmentation can beperformed by splitting the signal at time instances where signal amplitude orfrequency change. in this paper, the signal is initially decomposed into signals withdifferent frequency bands using wavelet transform. then, fractal dimension of thed...

In the fluorescence detection system, noise will affect the sensitivity of the system. The method using Stationary Wavelet Transform to de-noise fluorescence signals based on adaptive wavelet entropy is studied. The de-noising effects of dbN families are compared, and then the db7 wavelet is chosen as the optimal wavelet. The noised fluorescence signal is decomposed at 5 levels via Discrete Wav...

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...