Multi-dimensional Vector Ghost Imaging Video Based on Bidirectional Predictive Interpolation

doi:10.12068/j.issn.1005-3026.2022.07.004

Abstract

Abstract: To further improve the quality of moving object ghost image videos， a real-time imaging algorithm based on bidirectional predictive interpolation for multi-dimensional vector ghost image video is proposed according to the correlation characteristics between each frame in the video. That is to say， the multi-dimensional vector Walsh transform with energy concentration is used to divide a certain number of multi-dimensional Walsh basis patterns into fewer groups， doubling the effective basis patterns of each group， and then acting on the target object respectively. After reconstruction， the number of interframe images with better imaging quality is less， and then the intermediate frames are obtained by bidirectional predictive interpolation. Using this algorithm， the ghost image video of moving object can be realized in real time by acting on the object with 64×64 pixels. With the same sampling quantity and sampling time， high-quality reconstruction can be achieved and better quality ghost imaging video can be obtained.

Key words: ghost imaging of moving objects; multi-dimensional vector transformation; bidirectional prediction; interpolation; high quality reconstruction

CLC Number:

TN919.81

LIU Yue，SANG Ai-jun，SONG Li-jun，WANG Shi-gang. Multi-dimensional Vector Ghost Imaging Video Based on Bidirectional Predictive Interpolation[J]. Journal of Northeastern University(Natural Science), 2022, 43(7): 937-943.

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