Harmonic wavelet transform

About: Harmonic wavelet transform is a research topic. Over the lifetime, 9602 publications have been published within this topic receiving 247336 citations.

Feature level fusion of multimodal medical images in lifting wavelet transform domain

Abstract: A method for feature level image fusion for multimodal medical images in second generation wavelet domain (lifting wavelet transform domain) is proposed. The feature fused is edge and boundary information of input images that is extracted using wavelet transform modulus maxima criterion. The image fusion performance is evaluated by standard deviation, entropy, cross entropy and gradient parameters. Experimental results show that the proposed method gives better results for image fusion as image contrast, average information content and detail information of fused image are increased. This method has further advantages of fast implementation, flexibility, saving of auxiliary memory, property of perfect reconstruction and simplicity as we have used lifting wavelet transform. The reduction in computational complexity has been achieved by a factor of two as compared to the nonlifted wavelet transform.

Fractional Fourier transform of the Gaussian and fractional domain signal support

Abstract: The fractional Fourier transform (FrFT) provides an important extension to conventional Fourier theory for the analysis and synthesis of linear chirp signals. It is a parameterised transform which can be used to provide extremely compact representations. The representation is maximally compressed when the transform parameter, /spl alpha/, is matched to the chirp rate of the input signal. Existing proofs are extended to demonstrate that the fractional Fourier transform of the Gaussian function also has Gaussian support. Furthermore, expressions are developed which allow calculation of the spread of the signal representation for a Gaussian windowed linear chirp signal in any fractional domain. Both continuous and discrete cases are considered. The fractional domains exhibiting minimum and maximum support for a given signal define the limit on joint time-frequency resolution available under the FrFT. This is equated with a restatement of the uncertainty principle for linear chirp signals and the fractional Fourier domains. The calculated values for the fractional domain support are tested empirically through comparison with the discrete transform output for a synthetic signal with known parameters. It is shown that the same expressions are appropriate for predicting the support of the ordinary Fourier transform of a Gaussian windowed linear chirp signal.

Gray Level Co-Occurrence Matrix Computation Based On Haar Wavelet

Abstract: In this paper, a new computation for gray level co-occurrence matrix (GLCM) is proposed. The aim is to reduce the computation burden of the original GLCM computation. The proposed computation will be based on Haar wavelet transform. Haar wavelet transform is chosen because the resulting wavelet bands are strongly correlated with the orientation elements in the GLCM computation. The second reason is because the total pixel entries for Haar wavelet transform is always minimum. Thus, the GLCM computation burden can be reduced. The proposed computation is tested with the classification performance of the Brodatz texture images. Although the aim is to achieve at least similar performance with the original GLCM computation, the proposed computation gives a slightly better performance compare to the original GLCM computation.

A new polar Fourier transform for computer-aided tomography and spotlight synthetic aperture radar

Abstract: An algorithm for calculating the Fourier transform of certain discrete measures supported on a two-dimensional polar grid is described. The algorithm utilizes a modified Bluestein chirp algorithm to directly calculate the Fourier transform values over a rectangular grid. Applications to computer-aided tomography and spotlight synthetic aperture radar are described. >