Autofocus algorithm

Abstract

The invention discloses an autofocus algorithm, which comprises the following steps: collecting two consecutive focusing images of a target object, and respectively drawing a graph of a focusing evaluation function of the two focusing images; finding peak points F1 and F2 in the two graph; then, fitting the curves in the two graphs to find the peak point F0 after obtaining a fitted curve; comparing the positions of the focus lens where the F and F points are located, starting from the smaller position point, The larger position point is the end point, so that the focusing lens where the F1 andF2 are located; using the smaller position as a starting point and the larger position as a final point so that the focusing lens walks to the final point from the starting point with a step size SW,and the maximum value of the focusing evaluation function and the position of the focus lens are recorded; search is carried out back and forth repeatedly near the maximum value point; search is finished until the step size of the stepper motor is reduced to a set step size; at the moment, the focus lens stops at the maximum value Fmn of the focusing evaluation function, and the position of the focus lens is Wmn; the sizes of the Fmn and Fo are compared; if |Fmn-F0| is not greater than delta, the focusing process is finished; and if |Fmn-F0| is greater than delta, a preset step size is reduced to continue to search.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an automatic focusing algorithm. Background technique [0002] An ideal sharpness evaluation function should have unimodality, unbiasedness and good stability. The autofocus method based on the curve fitting of the focus evaluation function can quickly find the maximum value point of the evaluation function, but due to the interference of local extreme values, and the search is only a quick search of the whole process, this maximum point may not be the actual peak point, so The focusing efficiency is relatively low. Therefore, it is necessary to design a focusing algorithm that can solve the above problems. Contents of the invention [0003] The present invention is made to solve the above problems, and the purpose is to provide an automatic focusing algorithm. [0004] The present invention provides a kind of automatic focusing algorithm, has such featu...

AI Technical Summary

Problems solved by technology

The autofocus method based on the curve fitting of the focus evaluation function can quickly find the maximum value point of the evaluation function, but due to the interference of local extreme values, and the search is only a quick search of the whole process, this maximum point may not be the actual peak point, so Focus efficiency is relatively low

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