TITLE:
Efficiency Analysis of the Autofocusing Algorithm Based on Orthogonal Transforms
AUTHORS:
Przemysław Śliwiński, Krzysztof Berezowski, Piotr Patronik, Paweł Wachel
KEYWORDS:
Auto-Focusing; Image Variance; Discrete Orthogonal Transforms; Word-Length Selection; Architectural Performance Evaluation
JOURNAL NAME:
Journal of Computer and Communications,
Vol.1 No.6,
November
26,
2013
ABSTRACT:
Efficiency of
the autofocusing algorithm implementations based on various orthogonal
transforms is examined. The algorithm uses the variance of an
image acquired by a sensor as a focus function. To compute the estimate of the
variance we exploit the equivalence between that
estimate and the image orthogonal expansion. Energy consumption of three implementations
exploiting either of the following fast orthogonal transforms: the discrete
cosine, the Walsh-Hadamard, and the Haar
wavelet one, is evaluated and compared. Furthermore, it is conjectured that the
computation precision can considerably
be reduced if the image is heavily corrupted by the noise, and a simple problem
of optimal word bit-length selection with respect to the signal variance is
analyzed.