Abstract
Three-dimensional (3D) polarimetric integral imaging (InIm) to extract the 3D polarimetric information of objects in photon-starved conditions is investigated using a low noise visible range camera and a long wave infrared (LWIR) range camera, and the performance between the two sensors is compared. Stokes polarization parameters and degree of polarization (DoP) are calculated to extract the polarimetric information of the 3D scene while integral imaging reconstruction provides depth information and improves the performance of low-light imaging tasks. An LWIR wire grid polarizer and a linear polarizer film are used as polarimetric objects for the LWIR range and visible range cameras, respectively. To account for a limited number of photons per pixel using the visible range camera in low light conditions, we apply a mathematical restoration model at each elemental image of visible camera to enhance the signal. We show that the low noise visible range camera may outperform the LWIR camera in detection of polarimetric objects under low illumination conditions. Our experiments indicate that for 3D polarimetric measurements under photon-starved conditions, visible range sensing may produce a signal-to-noise ratio (SNR) that is not lower than the LWIR range sensing. We derive the probability density function (PDF) of the 2D and 3D degree of polarization (DoP) images and show that the theoretical model demonstrates agreement to that of the experimentally obtained results. To the best of our knowledge, this is the first report comparing the polarimetric imaging performance between visible range and infrared (IR) range sensors under photon-starved conditions and the relevant statistical models of 3D polarimetric integral imaging.
Highlights
Polarimetric imaging has been used in many applications such as object recognition, materials classification, and segmentation [1,2,3]
Passive three-dimensional (3D) polarimetric integral imaging (InIm) [8,9,10,11] is one of the prominent techniques to overcome the aforementioned issues with visible cameras operating in photon-starved conditions. 3D InIm [12,13,14,15,16,17,18,19,20,21,22] is performed by recording two-dimensional (2D) images from different perspectives, reconstructing the three-dimensional (3D) scene through either optical or computational reconstruction methods
The 3D scene consists of a linear polarizer film, a mannequin, and test tubes filled with hot water to provide an IR source, as shown by a reference image taken in high illumination conditions using the low noise visible range camera (Hamamatsu C11440-42U) by Fig. 1(a)
Summary
Polarimetric imaging has been used in many applications such as object recognition, materials classification, and segmentation [1,2,3]. Four quantities of Stokes parameters (S0, S1, S2 and S3) are required to measure the DoP These quantities can be recorded by placing polarizing elements in front of an image sensor, and recording images with different orientations of the polarizing elements. Passive three-dimensional (3D) polarimetric integral imaging (InIm) [8,9,10,11] is one of the prominent techniques to overcome the aforementioned issues with visible cameras operating in photon-starved conditions. 3D InIm [12,13,14,15,16,17,18,19,20,21,22] is performed by recording two-dimensional (2D) images from different perspectives, reconstructing the three-dimensional (3D) scene through either optical or computational reconstruction methods. The computational reconstruction process is performed by the back projection of the optical rays through a virtual pinhole to the desired reconstruction distance [23]
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