The photonics integrated interference imaging technique has attracted intensive attention because of its superior imaging performance and structural compactness. Traditional architecture designs of the photonics integrated interference imaging systems are of radial patterns and rectangular patterns. Due to their large lens intervals, the resulting frequency distributions are insufficient to satisfy the Nyquist sampling conditions. In this paper, a new structural type of hexagonal arrays is designed, which has a dense lens distribution. Two paring methods are developed for the radial baselines and lateral baselines, and they can be selected according to the actual frequency bands of interest. The optical performance of different arrays is analyzed, and the hexagonal array is proved superior over the radial pattern and rectangular pattern in terms of point spread functions. A reconstruction algorithm based on the compressed sensing theory is proposed to restore salient images from insufficiently sampled signals. A measurement matrix consistent with the structural design is applied to avoid data regridding. Experimental results demonstrate that the imaging resolution is improved remarkably with respect to the original images. INDEX TERMS Interference imaging, baseline pairing, compressed sensing, image reconstruction.

The high dimension and complexity of feature descriptor of Scale Invariant Feature Transform (SIFT), not only occupy the memory spaces, but also influence the speed of feature matching. We adopt the statistic feature point’s neighbor gradient method, the local statistic area is constructed by 8 concentric square ring feature of points-centered, compute gradient of these pixels, and statistic gradient accumulated value of 8 directions, and then descending sort them, at last normalize them. The new feature descriptor descend dimension of feature from 128 to 64, the proposed method can improve matching speed and keep matching precision at the same time.

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