Premium
Automatic focusing by correlative methods
Author(s) -
Vollath D.
Publication year - 1987
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.1987.tb02839.x
Subject(s) - autocorrelation , focus (optics) , binary number , brightness , computer science , correlative , noise (video) , image (mathematics) , ergodic theory , contrast (vision) , segmentation , simple (philosophy) , artificial intelligence , metrology , algorithm , randomness , luminance , function (biology) , computer vision , pattern recognition (psychology) , mathematics , optics , physics , statistics , mathematical analysis , linguistics , philosophy , arithmetic , epistemology , evolutionary biology , biology
The possibility of focusing images by the autocorrelation function is explained. It can be shown that these techniques are less sensitive to disturbances by noise than others. Furthermore, focusing criteria derived from autocorrelation functions have different responses to image contrast. It has been shown that these focusing criteria can be determined using binary images and applying the laws of stochastic ergodic metrology. This leads to a large reduction in computing time. Moreover, an attempt was made to focus by means of binary images determined by simple segmentation. The experimental results show that such a focus criterion operates quite well. The criterion offers the advantage that brightness levels in the image can be chosen selectively for focusing.