Adaptive compressed photon counting 3D imaging based on wavelet trees and Hadamard multiplexing

Huidong Dai; Guohua Gu; Weiji He; Ling Ye; Tianyi Mao; Qian Chen

doi:10.1117/12.2272923

6 September 2017 Adaptive compressed photon counting 3D imaging based on wavelet trees and Hadamard multiplexing

Huidong Dai, Guohua Gu, Weiji He, Ling Ye, Tianyi Mao, Qian Chen

Author Affiliations +

Proceedings Volume 10410, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017; 104101A (2017) https://doi.org/10.1117/12.2272923
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

A photon counting 3D imaging system with short-pulsed structured illumination and a single-pixel photon counting detector is built. The proposed multiresolution photon counting 3D imaging technique acquires a high-resolution 3D image from a coarse image and details at successfully finer resolution sampled by Hadamard multiplexing along with the wavelet trees. The detected power is significant increased thanks to the Hadamard multiplexing. Both the required measurements and the reconstruction time can be significant reduced, which makes the proposed technique suitable for scenes with high spatial resolution. Since the depth map is retrieved through a linear inverse Hadamard transform instead of the computational intensive optimization problems performed in CS, the time consumed to retrieve the depth map can be also reduced, and thus it will be suitable for applications of real-time compressed 3D imaging such as object tracking. Even though the resolution of the final 3D image can be high, the number of measurements remains small due to the adaptivity of the wavelet-trees-based sampling strategy. The adaptive sampling technique is quality oriented, allowing more control over the image quality. The experimental results indicate that both the intensity image and depth map of a scene at resolutions up to 512×512 pixels can be acquired and retrieved with practical times as low as 17 seconds.

Citation Download Citation

Huidong Dai, Guohua Gu, Weiji He, Ling Ye, Tianyi Mao, and Qian Chen "Adaptive compressed photon counting 3D imaging based on wavelet trees and Hadamard multiplexing", Proc. SPIE 10410, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017, 104101A (6 September 2017); https://doi.org/10.1117/12.2272923

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Photon counting

3D acquisition

Multiplexing

Wavelets

3D metrology

Image acquisition

Keywords/Phrases

Search In:

Publication Years