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IIT Madras And Rice University Researchers Develop Algorithms For Lensless, Miniature Cameras

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

IIT Madras & Rice University Researchers develop Algorithms for Lensless, Miniature Cameras

Share 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.

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