A multiresolution approach based on a modified wavelet transform called the tree-structured wavelet transform or wavelet packets is proposed. The development of this transform is motivated by the observation that a large class of natural textures can be modeled as quasi-periodic signals whose dominant frequencies are located in the middle frequency channels. With the transform, it is possible t...

An Image Resolution Enhancement Technique based on Interpolation of the high frequency sub-band of colour images obtained by Discrete Wavelet Transform and the input colour image is proposed in this paper. Interpolation determines the intermediate values on the basis of observed values. One of the commonly used interpolation technique is Bicubic Interpolation. The edges are enhanced by introduc...

In this paper we propose a new steganography technique which embeds secrete color image into color cover work in frequency domain. Unlike the spatial domain approach, secrete image or data are embedded in the low frequency coefficients resulted from Discrete Wavelet Transform, as it is much sensitive to Human Visual System several researchers are not preferring to embed data in low frequency co...

In this correspondence I propose an image super-resolution technique based on interpolation of high frequency sub-band images obtained by Discrete Wavelet Transform on input image. In those sub-bands edges are enhanced by introducing an intermediate stage by using Stationary Wavelet Transform. The wavelet transform is applied in order to decompose image into different subbands. In those sub-ban...

The fractional Fourier transform is a new concept in the theory of time-frequency representations. Closely linked to the Wigner distribution through the Radon transform, it introduces frequency-time hybrid domains in which the signal and the noise could be interwoven differently than in either the time or the frequency domain. The fractional transform breaks down a signal into elementary chirp ...

In this paper, a multimodal image fusion algorithm based on multiresolution transform and particle swarm optimization (PSO) is proposed. Firstly, the source images are decomposed into low-frequency coefficients and high-frequency coefficients by the dual-tree complex wavelet transform (DTCWT). Then, the high-frequency coefficients are fused by the maximum selection fusion rule. The low-frequenc...

In this paper, we examine robust feature extraction methods for automatic speech recognition (ASR) in noise-distorted environments. Several perceptual experiments have shown that the range between 1 and 10 Hz of modulation frequency band is important for ASR. Combining the coefficients of multi-resolutional Fourier transform to split the important modulation frequency band for ASR into several ...

Wigner Ville Transform is introduced as a suitable tool for the analysis of the speech signal, as it allows making a correct representation of the signal energy. First, we give a mathematical formulation of the Wigner Ville Transform of a stationary model of voiced speech. The speech model is expressed as a linear combination of the harmonic frequencies of fundamental frequency of the voiced sp...

Hilbert transform is a basic tool in constructing analytical signals for a various applications such as amplitude modulation, envelope and instantaneous frequency analysis, quadrature decoding, shift-invariant multi-rate signal processing and Hilbert-Huang decomposition. This work introduces a complex Hilbert transform (CHT) filter, where the real and imaginary parts are a Hilbert transform pai...

The windowed Fourier transform (short time Fourier transform) and the S-transform are widely used signal processing tools for extracting frequency information from non-stationary signals. Previously, the windowed Fourier transform had been adopted for signals on graphs and has been shown to be very useful for extracting vertex-frequency information from graphs. However, high computational compl...