基于小波树和哈达玛矩阵的自适应快速三维压缩成像方法

针对光子计数系统实现三维成像速度缓慢的问题，提出一种基于小波树和哈达玛矩阵的自适应快速三维压缩成像方法。利用哈达玛矩阵调制投影图案提高采样效率，被调制的短脉冲结构光照射场景，单像素光子计数探测器采集回波。通过分析低分辨率图像的小波树选择采样区域，使用哈达玛矩阵调制所选采样区域得到的投影图案，可采集图像细节，多阶段采样后利用哈达玛反变换恢复出高分辨率图像。实验结果表明，采集并恢复出一幅512×512像素的三维图像的时间最快可达到41 s。

Fast adaptive compressed 3D imaging based on wavelet trees and Hadamard matrix

Aiming at the problem of slow 3D imaging speed in photon counting system, a method of fast adaptive compressed 3D imaging method based on wavelet trees and Hadamard matrix was proposed. The sampling efficiency was improved by modulating projective patterns with Hadamard matrix, the scene was illuminated with modulated short-pulsed structured light, and the echoes were collected by the single-pixel photon counting detector. The sample area was selected by analyzing the wavelet trees of coarser images. With the patterns projected from the sample area modulated by Hadamard matrix, image details could be sampled. After the multistage sampling, the high-resolution image could be recovered with Hadamard inverse transform. The experimental results indicate that a 3D image at resolution up to 512×512 pixel can be acquired and retrieved with practical time as low as 41 s.