Binning-based local-threshold filtering for enhancement of underwater 3D gated range-intensity correlation imaging
Yuqing Yang, Xinwei Wang, Liang Sun, Xin Zhong, Pingshun Lei, Jianan Chen, Jun He, Yan Zhou
Abstract
3D gated range-intensity correlation imaging (GRICI) can reconstruct a 3D scene with high range resolution in real time. However, in the applications of underwater range-gated imaging, targets with low reflectivity or at a far distance typically have a low signal-to-noise ratio (SNR), especially in turbid water. Usually, a global threshold is set to suppress noise in gated images, which easily results in data holes in the degraded depth map reconstructed by 3D GRICI. To solve the problem, we have proposed a binning-based local-threshold filtering (BLF) algorithm to fill depth data holes. Firstly, raw gated images are added to obtain a sum image, and global threshold filtering and pixel binning for the sum image are used to obtain a reference image. Secondly, hole pixels can be registered according to the reference image. Finally, a smaller local threshold is reset for the hole pixels, and then a repaired depth map is given by 3D GRICI. The experimental results have shown that the proposed method can effectively fill depth data holes and the peak signal-to-noise ratio of the repaired depth map is increased from 10.23 dB to 22.45 dB by suppressing water noise with the improved range resolution from 6.25 mm to 4.12 mm. In addition, the 3D depth of viewing is enlarged, and the limit detection distance is increased by 21% in experiment. The research can promote the practical applications of 3D GRICI.