Computational Tutorial of Steepest Descent Method and Its Implementation in Digital Image Processing
Computational Tutorial of Steepest Descent Method and Its Implementation in Digital Image Processing
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2013
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eng
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application/pdf
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16 pages
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The ECATI E-magazine, ECTI Association 7, 1 (January – March 2013)
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Abstract
In the last decade, optimization techniques have extensively come up as one of
principal signal processing techniques, which are used for solving many previous
intractable problems in both digital signal processing (DSP) problems and digital
image processing (DIP) problem. Due to its low computational complexity and
uncomplicated implementation, the Gradient Descent (GD) method [1] is one of the
most popular optimization methods for problems, which can be formulated as a
differentiable multivariable functions. The GD method is ubiquitously used from
basic to advanced researches. First, this paper presents the concept of GD method and
its implementations for general mathematical problems. Next, the computation of GD
processes is shown step by step with the aim to understand the effect of important
parameters (such as its initial value and step size) to the performance of GD. Later,
the computational concept of GD method for DIP problems [2-5] is formulated and
the computation of GD is demonstrated step by step. The effect of the initial value and
the step size to the performance of GD method in DIP is also presented.