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Research of Image Sharpness Assessment Algorithm for Autofocus

With the wide application of imaging system in security monitoring, aerospace, medical image and other fields, how to capture the clear image of the target in real time and automatically is particularly important. Image sharpness evaluation function is the key to evaluate the imaging quality of various imaging systems. The spatial gradient evaluation algorithm is based on the direct processing of image pixels, and the calculation is simple and intuitive. In this paper, we compare the performance of image sharpness evaluation functions in four spatial domains through two sets of atlases with different background richness. Experiments show that Benner algorithm has high scene adaptability and strong anti-jamming ability; Laplace algorithm has high sensitivity and can get results quickly in different size images; Tenengrad algorithm can reduce the occurrence of local extremum after selecting a certain threshold; Robert algorithm has poor unimodality and accuracy in two sets of atlas test.