Title :
Application of stochastic counterpart optimization to contrast-detection autofocusing
Author :
Sliwinski, Przemyslaw ; Wachel, Pawel
Author_Institution :
Inst. of Comput. Eng., Control & Robot., Wroclaw Univ. of Technol., Wroclaw, Poland
Abstract :
A simple model for the contrast-detection autofocusing problem is considered. The variance of the image is examined as a focus function. We prove that the standard convergence rate of the variance estimate (empirical focus function) of order O(T-1), where T is a (relative) sensor size, allows direct application of the golden-section search algorithm to the empirical focus function.
Keywords :
computer vision; convergence; focusing; image sensors; optimisation; search problems; stochastic processes; contrast-detection autofocusing problem; convergence rate; empirical focus function; golden-section search algorithm; image variance; sensor size; stochastic counterpart optimization; variance estimate; Approximation algorithms; Correlation; Lenses; Optimization; Reactive power; Splines (mathematics); Stochastic processes; Focus function; convergence; empirical focus function; golden-section search; image variance; variance estimation;
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
DOI :
10.1109/ICACCI.2013.6637193
