Abstract

Thermal imaging can easily see through smoke and dust. It is a useful technique in the military and industrial fields. However, thermal imaging can also be blocked by heavy mist or gases with high emissivity such as ${\mathrm{CO}}_2$. Allowing a thermal camera to see through these obstacles is in high demand. In this paper, we modeled the occlusion problem in thermal imaging and proposed an algorithm to image the objects through mist and foliage. We built a system to capture the thermal light field camera. We took thermal reflection and absorption of the obstacles into consideration. We removed the obstacle part in thermal images by estimating the intensity of infrared radiation. Then, we refocused the thermal images on the specific depth of the object for reconstruction. The experiment’s results show that a proposed algorithm can reconstruct the occluded objects in a clear shape while blurring the obstacles. Based on the thermal occlusion model and refocusing, the thermal camera can image a human through mist and foliage.

© 2019 Optical Society of America

Human detection in occluded scenes through optically inspired multi-camera image fusion

Maryam Ghaneizad, Zahra Kavehvash, and Hamid Aghajan
J. Opt. Soc. Am. A 34(6) 856-869 (2017)

See-through integral imaging display with background occlusion capability

Yuta Yamaguchi and Yasuhiro Takaki
Appl. Opt. 55(3) A144-A149 (2016)

Detection and removal of fence occlusions in an image using a video of the static/dynamic scene

Sankaraganesh Jonna, Krishna K. Nakka, Vrushali S. Khasare, Rajiv R. Sahay, and Mohan S. Kankanhalli
J. Opt. Soc. Am. A 33(10) 1917-1930 (2016)

Three-dimensional profilometric reconstruction using flexible sensing integral imaging and occlusion removal

Xin Shen, Adam Markman, and Bahram Javidi
Appl. Opt. 56(9) D151-D157 (2017)

Robust depth estimation for multi-occlusion in light-field images

Wei Ai, Sen Xiang, and Li Yu
Opt. Express 27(17) 24793-24807 (2019)