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Computational Imaging Enables a Camera to Use a Window as a Lens

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An engineering team from the University of Utah has found a way to use a regular pane of glass or any see-through window as a camera lens. The technique uses a computer algorithm, instead of a lens, to identify, decode, and focus the image.

Professor Rajesh Menon and his team used their method to take a picture of the University of Utah’s “U” logo and a video of an animated stick figure, both displayed on an LED light board. The researchers placed an inexpensive, off-the-shelf image sensor (with no lens) on the edge of a plexiglass window. Reflective tape was wrapped around the edge of the window.

University of Utah electrical and computer engineering associate professor Rajesh Menon.
University of Utah electrical and computer engineering associate professor Rajesh Menon has discovered a way to create a camera in which a regular pane of glass or any see-through window can become the lens. Courtesy of Dan Hixson/University of Utah College of Engineering.

The sensor was pointed into the window, and the light board was positioned in front of the window at an angle of 90 degrees from the sensor. Light rays from the scene were redirected by the rough surface of the window into the acceptance angle of the image sensor, and computational methods were used to reconstruct the scene information.

Most of the light coming from the object in the image passed through the glass; but just enough light — about 1 percent — scattered through the window and into the camera sensor for the algorithm to decode the image.

The resulting image was low-resolution but recognizable. The researchers said that with judicious choice of geometric parameters, the system could be optimized for image contrast and angular field of view.

Applications for the team’s lensless imaging technique could include security cameras built into a home during construction by using the windows as lenses. The technique could also be used in augmented-reality (AR) goggles to reduce their bulk. With current AR glasses, cameras have to be pointed at the user’s eyes in order to track their positions. With this technology, they could be positioned on the sides of the lens.

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Multiple cameras could be placed along the edges of a car windshield to capture information. The lensless technology also could be used in retinal or other biometric scanners, which typically have cameras pointed at the eye.

“It's not a one-size-fits-all solution, but it opens up an interesting way to think about imaging systems,” Menon said.

Menon and his team plan to develop the system further, to give it the ability to produce 3D images and higher color resolution and to photograph objects illuminated by regular household light, rather than by a light board.

The research was published in Optics Express, a publication of OSA, The Optical Society (doi: 10.1364/OE.26.022826). 


University of Utah electrical and computer engineering professor Rajesh Menon and his team have developed a lensless camera. Courtesy of University of Utah.

Interested in learning more about computational imaging? Photonics Media is offering a free webinar on this topic on October 16, 2018. For more information and to register, visit www.photonics.com/ w150.

Published: August 2018
Glossary
machine vision
Machine vision, also known as computer vision or computer sight, refers to the technology that enables machines, typically computers, to interpret and understand visual information from the world, much like the human visual system. It involves the development and application of algorithms and systems that allow machines to acquire, process, analyze, and make decisions based on visual data. Key aspects of machine vision include: Image acquisition: Machine vision systems use various...
computational imaging
Computational imaging refers to the use of computational techniques, algorithms, and hardware to enhance or enable imaging capabilities beyond what traditional optical systems can achieve. It involves the integration of digital processing with imaging systems to improve image quality, extract additional information from captured data, or enable novel imaging functionalities. Principles: Computational imaging combines optics, digital signal processing, and algorithms to manipulate and...
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