Search

Structured illumination microscopy(SIM) is capable of providing super-resolution imaging. It breaks the diffraction limit by moving the high-frequency information of objects into the detectable frequency band of the optical imaging system via frequency mixing. Due to its attractive advantages, such as low intensity illumination, independence of particular fluorescent dyes, and rapid wide-field imaging capability, SIM has become the most popular technique for super-resolution imaging of living cells. This paper first systematically summarizes advances in the development of SIM and introduces corresponding principles at the same time. Then, two novel techniques of SIM developed by our group, including the single-photon excited super-resolution microscopy based on spectral unmixing and the two-photon excited super-resolution microscopy combined with adaptive optics, are particularly introduced in detail. At last, the recent applications and future directions of SIM in biological imaging are briefly discussed.

A general hierarchical particle filtering framework for designing an optimal proposal distribution is proposed. The essential idea is to augment a second filter's estimate into the proposal distribution design. Based on this framework,a novel algorithm for robust and efficient visual tracking is given. The algorithm using hierarchical particle filtering procedures at each level and can efficiently extract high-confidence regions through video frames by exploiting the temporal consistency of region confidences. Comparisons with the mean shift tracker and a generic particle filter shows the advantages and limitations of the new approach.

Utilizing the contourlet's advantages of multiscale,localization,directionality and anisotropy,a multifocus image fusion algorithm based on directional windows statistics in contourlet domain is developed.Source images are firstly decomposed to the domain of the contourlet transform,then the image fusion is implemented in subbands with different scale and direction combining with region statistics.Regional variance and local energy are adopted as fusion rules in lowpass and highpass subbands,respectively.And the fused image is obtained through inverse transform.Compared to traditional gradient pyramid algorithm and wavelet based algorithm,experimental results show that the directional windows method can detect image features more effectively and the fused image has better subjective visual effect.