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This book describes how a key signal/image processing algorithm -
that of the fast Hartley transform (FHT) or, via a simple
conversion routine between their outputs, of the real-data version
of the ubiquitous fast Fourier transform (FFT) - might best be
formulated to facilitate computationally-efficient solutions. The
author discusses this for both 1-D (such as required, for example,
for the spectrum analysis of audio signals) and m-D (such as
required, for example, for the compression of noisy 2-D images or
the watermarking of 3-D video signals) cases, but requiring few
computing resources (i.e. low arithmetic/memory/power requirements,
etc.). This is particularly relevant for those application areas,
such as mobile communications, where the available silicon
resources (as well as the battery-life) are expected to be limited.
The aim of this monograph, where silicon-based computing technology
and a resource-constrained environment is assumed and the data is
real-valued in nature, has thus been to seek solutions that best
match the actual problem needing to be solved.
This book describes how a key signal/image processing algorithm -
that of the fast Hartley transform (FHT) or, via a simple
conversion routine between their outputs, of the real-data version
of the ubiquitous fast Fourier transform (FFT) - might best be
formulated to facilitate computationally-efficient solutions. The
author discusses this for both 1-D (such as required, for example,
for the spectrum analysis of audio signals) and m-D (such as
required, for example, for the compression of noisy 2-D images or
the watermarking of 3-D video signals) cases, but requiring few
computing resources (i.e. low arithmetic/memory/power requirements,
etc.). This is particularly relevant for those application areas,
such as mobile communications, where the available silicon
resources (as well as the battery-life) are expected to be limited.
The aim of this monograph, where silicon-based computing technology
and a resource-constrained environment is assumed and the data is
real-valued in nature, has thus been to seek solutions that best
match the actual problem needing to be solved.
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