Friday, December 22, 2017

DiffuserCam - Continued

BusinessWire: UCB keeps promoting its DiffuserCam project first presented in October. An open source paper "DiffuserCam: lensless single-exposure 3D imaging" by Nick Antipa, Grace Kuo, Reinhard Heckel, Ben Mildenhall, Emrah Bostan, Ren Ng, and Laura Waller is published in OSA Optica. The camera open-source code is also available on GitHub.

"...the researchers show that the DiffuserCam can be used to reconstruct 100 million voxels, or 3D pixels, from a 1.3-megapixel (1.3 million pixels) image without any scanning.

...Although the hardware is simple, the software it uses to reconstruct high resolution 3D images is very complex.

The DiffuserCam is a relative of the light field camera, which captures how much light is striking a pixel on the image sensor as well as the angle from which the light hits that pixel.

Until now, light field cameras have been limited in spatial resolution because some spatial information is lost while collecting the directional information. Another drawback of these cameras is that the microlens arrays are expensive and must be customized for a particular camera or optical components used for imaging.

using random bumps in privacy glass stickers, Scotch tape or plastic conference badge holders, allowed the researchers to improve on traditional light field camera capabilities by using compressed sensing to avoid the typical loss of resolution that comes with microlens arrays.

Although other light field cameras use lens arrays that are precisely designed and aligned, the exact size and shape of the bumps in the new camera’s diffuser are unknown. This means that a few images of a moving point of light must be acquired to calibrate the software prior to imaging. The researchers are working on a way to eliminate this calibration step by using the raw data for calibration. They also want to improve the accuracy of the software and make the 3D reconstruction faster.

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