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Journal ArticleDOI

Discrete Hartley transform

Ronald N. Bracewell
- 01 Dec 1983 - 
- Vol. 73, Iss: 12, pp 1832-1835
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TLDR
The discrete Hartley transform (DHT) resembles the discrete Fourier transform (DFT) but is free from two characteristics of the DFT that are sometimes computationally undesirable and promises to speed up Fourier-transform calculations.
Abstract
The discrete Hartley transform (DHT) resembles the discrete Fourier transform (DFT) but is free from two characteristics of the DFT that are sometimes computationally undesirable. The inverse DHT is identical with the direct transform, and so it is not necessary to keep track of the +i and −i versions as with the DFT. Also, the DHT has real rather than complex values and thus does not require provision for complex arithmetic or separately managed storage for real and imaginary parts. Nevertheless, the DFT is directly obtainable from the DHT by a simple additive operation. In most image-processing applications the convolution of two data sequences f1 and f2 is given by DHT of [(DHT of f1) × (DHT of f2)], which is a rather simpler algorithm than the DFT permits, especially if images are. to be manipulated in two dimensions. It permits faster computing. Since the speed of the fast Fourier transform depends on the number of multiplications, and since one complex multiplication equals four real multiplications, a fast Hartley transform also promises to speed up Fourier-transform calculations. The name discrete Hartley transform is proposed because the DHT bears the same relation to an integral transform described by Hartley [ HartleyR. V. L., Proc. IRE30, 144 ( 1942)] as the DFT bears to the Fourier transform.

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Citations
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Journal ArticleDOI

Pathological liver segmentation using stochastic resonance and cellular automata

TL;DR: Qualitative and quantitative evaluation performed on the proposed segmentation method for reconstructing the liver surface in low contrast computed tomography show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method.
Journal ArticleDOI

A prime factor fast W transform algorithm

TL;DR: A method for converting any nesting DFT algorithm to the type-I discrete W transform (DWT-I) is introduced and is more efficient that either WFTA or PFA for large N, and it is more flexible for the choice of transform length.
Journal ArticleDOI

A PCA-based approach for brain aneurysm segmentation

TL;DR: A stochastic resonance based methodology in discrete Hartley transform domain is developed to enhance the contrast of a selected angiographic image for patch placement, and a multi-scale adaptive principal component analysis based method is proposed that estimates the phase map of input images.
Book

Partitioned convolution algorithms for real-time auralization

TL;DR: This thesis considers three different classes of partitioned convolution algorithms for the use in real-time auralization: uniformly and non-uniformly partitioned filters, as well as unpartitioned filters.
Journal ArticleDOI

Structured fast Hartley transform algorithms

TL;DR: A decimation-in-frequency algorithm with a similar flowgraph is obtained that is identical to that of another FHT algorithm recently proposed.
References
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Book

The Fourier Transform and Its Applications

TL;DR: In this paper, the authors provide a broad overview of Fourier Transform and its relation with the FFT and the Hartley Transform, as well as the Laplace Transform and the Laplacian Transform.
Journal ArticleDOI

A More Symmetrical Fourier Analysis Applied to Transmission Problems

TL;DR: In this article, the Fourier identity is expressed in a more symmetrical form which leads to certain analogies between the function of the original variable and its transform, and it permits a function of time to be analyzed into two independent sets of sinusoidal components, one of which is represented in terms of positive frequencies, and the other of negative.
Journal ArticleDOI

Harmonic analysis with a real frequency function—I. aperiodic case

TL;DR: An integral transform which converts a real spatial (or temporal) function into a real frequency function is introduced in this paper, and the properties of this transform are investigated, and it is concluded that this transform is parallel to the Fourier transform and may be applied to all fields in which the FFT has been successfully applied.