Indian, US researchers develop algorithms for lensless, miniature cameras with futuristic applications
They offer imaging capabilities similar to conventional cameras, but at much lesser weight, cost and nearly-flat cameras.
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Updated: May 17, 2021, 05:10 PM IST
Researchers from IIT Madras and Rice University, USA, have developed algorithms for lensless, miniature cameras that have applications in Augmented/Virtual reality, security, smart wearables, robotics among others. Lensless cameras are touted to be the future of miniature imaging technology, as they offer imaging capabilities similar to conventional cameras, but at much lesser weight, cost and nearly-flat cameras.
In conventional cameras, the lens enables light to be focussed onto an imaging sensor, which captures a sharp, detailed photograph. However, in lensless cameras the light will fall on many pixels (giving a blurred image), from which the final image has to be derived via a software.
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The Team used ‘deep learning’ to develop a reconstruction algorithm called ‘FlatNet’ for lensless cameras which produces photorealistic images from lensless captures, reducing the gap in photograph quality between conventional cameras and ultra-thin lensless cameras
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Chennai: Indian Institute of Technology Madras and Rice University, U.S., have developed algorithms for lensless, miniature cameras. Such lensless cameras have numerous vision applications in areas such as Augmented Reality (AR)/ Virtual Reality (VR), security, smart wearables and robotics where cost, form-factor, and weight are major constraints (see Figure 1).
Lensless cameras do not have a lens which, in a conventional camera, acts as a focusing element allowing the sensor to capture a sharp photograph of the scene. Due to the absence of this focusing element, the lensless camera captures a multiplexed or globally blurred measurement of the scene. IIT Madras and Rice University researchers have developed a deep learning algorithm for producing photo-realistic images from the blurred lensless capture.