Topic
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.
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Papers
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01 Jan 1999TL;DR: A method for efficiently using the properties of the DT-CWT in finding the directional and spatial/frequency characteristics of the patterns and classifying different texture patterns in terms of these characteristics is proposed.
Abstract: A new texture feature extraction method utilizing the dual-tree complex wavelet transform (DT-CWT) is introduced. The complex wavelet transform is a tool that uses a dual tree of wavelet filters to find the real and imaginary parts of complex wavelet coefficients. The approximate shift invariance, good directional selectivity, and computational efficiency properties of the DT-CWT make it a good candidate for representing the texture features. We propose a method for efficiently using the properties of the DT-CWT in finding the directional and spatial/frequency characteristics of the patterns and classifying different texture patterns in terms of these characteristics. Experimental results show that the proposed feature extraction and classification method is efficient in terms of the computational speed and retrieval accuracy.
64 citations
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TL;DR: A new method called fractional wavelet packet transform to encrypt images in this paper, in which fractional orders andWavelet packet filter are its two series of keys.
64 citations
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TL;DR: The method is an enhanced version of the algorithm of Caverhill and Clewlow (1992) and to adapt it to non-lognormal densities, which enables us to examine the impact of fat-tailed distribution on price.
Abstract: This paper presents an e±cient methodology for the discrete Asian options consistent with di®erent types of underlying densities, especially non-normal returns as suggested by the empirical literature (Mandelbrot (1963) and Fama (1965)). Based on Fast Fourier Transform, the method is an enhanced version of the algorithm of Caverhill and Clewlow (1992). The contribution of this paper is to improve their algorithm and to adapt it to non-lognormal densities. This enables us to examine the impact of fat-tailed distribution on price
64 citations
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TL;DR: In this paper, a nonlinear, invertible, low-level image processing transform based on combining the well-known Radon transform for image data, and the 1D cumulative distribution transform proposed earlier is described.
Abstract: Invertible image representation methods (transforms) are routinely employed as low-level image processing operations based on which feature extraction and recognition algorithms are developed. Most transforms in current use (e.g., Fourier, wavelet, and so on) are linear transforms and, by themselves, are unable to substantially simplify the representation of image classes for classification. Here, we describe a nonlinear, invertible, low-level image processing transform based on combining the well-known Radon transform for image data, and the 1D cumulative distribution transform proposed earlier. We describe a few of the properties of this new transform, and with both theoretical and experimental results show that it can often render certain problems linearly separable in a transform space.
64 citations
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15 Mar 2000TL;DR: In this article, a method for registering first and second images which are offset by an x and/or y displacement in sub-pixel locations is presented, which includes the steps of: multiplying the first image by a window function to create a first windowed image, transforming the first window image with a Fourier transform, multiplying the second image by the window function, and transforming the second windowing image with the Fourier transformation, and computing a collection of coordinate pairs from the two image Fourier transforms, such that at each coordinate pair the values of the first and the second
Abstract: Methods for registering first and second images which are offset by an x and/or y displacement in sub-pixel locations are provided. A preferred implementation of the methods includes the steps of: multiplying the first image by a window function to create a first windowed image; transforming the first windowed image with a Fourier transform to create a first image Fourier transform; multiplying the second image by the window function to create a second windowed image; transforming the second windowed image with a Fourier transform to create a second image Fourier transform; computing a collection of coordinate pairs from the first and second image Fourier transforms such that at each coordinate pair the values of the first and second image Fourier transforms are likely to have very little aliasing noise; computing an estimate of a linear Fourier phase relation between the-first and second image Fourier transforms using the Fourier phases of the first and second image Fourier transforms at the coordinate pairs in a minimum-least squares sense; and computing the displacements in the x and/or y directions from the linear Fourier phase relationship. Also provided are a computer program having computer readable program code and program storage device having a program of instructions for executing and performing the methods of the present invention, respectively.
64 citations