Abstract
Aiming at improving the speed and accuracy of auto-focus for telescope observation, algorithms for image estimation and auto-focus were investigated and are discussed in this article. Based on the image quality assessment, the auto-focusing process of the telescope system is realized by using the mountain-climb search method. Several evaluation functions were tested in different scenarios. It is demonstrated that the Tenengrad image estimation function (IEF) is suitable for an instant and accurate auto-focus process of the telescope. Furthermore, we implemented sampling and dynamic adaptive focusing window (ES-DAFW) methods with the Tenengrad IEF to enhance the sensitivity and accuracy of the auto-focus process. The experimental results showed that our ES-DATW method can provide more accurate results in less time for the auto-focus process compared to the conventional approaches, especially for a sparse image. These results promise significant applications to the auto-focusing of other telescopes with image quality assessment.
Funder
National Natural Science Foundation of China
Aeronautical Science Foundation of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
13 articles.
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