A new wavelet-based focus measure was proposed. High

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(Numerical Aperture) and low

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microscope image sequences were used to compare the performance of this focus measure with the classic and popular focus measures Normalized Variance

Entropy

Energy Laplace and other two Wavelet-based High Frequency focus measures. The robustness of these focus measures was also compared using image sequence corrupted by Gaussian white noise with that of standard deviations 25. Experimental results show that the proposed focus measure can provide significantly better depth resolution and accuracy than the comparing ones

and exhibit comparatively good robustness with Normalized Variance. A selective focusing technique for autofocusing on the three dimension microscale objects in different depth was developed. The results also show that this focus measure and selective autofocusing techniques can be widely applied to automated micromanipulation; and that autofocusing is of fundamental importance to automated micromanipulation

and focus measures are the key techniques.