The two-band discrete wavelet transform (DWT) provides an octave-band analysis in the frequency domain, but this might not be “optimal” for a given signal. The discrete wavelet packet transform (DWPT) provides a dictionary of bases over which one can search for an optimal representation (without constraining the analysis to an octave-band one) for the signal at hand. However, it is well known t...

In this paper, we propose an audio coder for high quality low bit-rate applications based on the wavelet-packet transform. The primary goal of the proposed coder will be to combine high quality reconstructed audio with shorter delay than existing methods while keeping the bit rate low. Present audio coders, such as MPEG, are capable of transparent or near-transparent monophonic CD quality at 12...

In this paper, an algorithm for wavelet packet trees that can systematically identify all bit allocations/best-basis selections on the lower convex hull of the rate-distortion curve is presented. The algorithm is applied to tree-structured vector quantizers used to code image subbands that result from the wavelet packet decomposition. This method is compared to optimal bit allocation for the di...

This paper presents a novel method for handwritten character recognition using wavelet packet transform and fuzzy logic. This method exploits the time-frequency localization and compression capability of wavelet packet transform, using the best basis algorithm to enhance the accuracy of recognition at the pixel level and the computational capability of fuzzy logic with linguistic variables, whi...

This paper presents a novel method for automatic handwritten character recognition by combining wavelet packet transform with neurofuzzy approach. The time-frequency localization and compression capability of wavelet packet transform using best-basis algorithm is used for feature extraction, enhancing the accuracy of recognition at pixel level. The best-basis algorithm automatically adapts the ...

Wavelet transform has been extensively used in machine fault diagnosis and prognosis owing to its strength to deal with non-stationary signals. The existing Wavelet transform based schemes for fault diagnosis employ wavelet decomposition of the entire vibration frequency which not only involve huge computational overhead in extracting the features but also increases the dimensionality of the fe...

Detection of gearing and bearing faults using vibration signals has been widely used for decades. A lot of methods of vibration signal processing for fault detection have been used, such as fast Fourier transform, Hilbert transform, wavelet and wavelet packet transform. In recent years, a new method for vibration signal processing, combining Hilbert transform and wavelet packet appeared, and ha...

Classification of texture images, especially those with different orientation and scale changes, is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation and scale invariant texture classification using log-polar wavelet signatures. The rotation and scale invariant feature extraction for a given image involves applying a l...

Recently discrete wavelet transform and wavelet packet has emerged as popular techniques for image compression. The wavelet transform is one of the major processing components of image compression. The results of the compression change as per the basis and tap of the wavelet used. This paper compares compression performance of Daubechies, Biorthogonal, Coiflets and other wavelets along with res...