IIT Madras & Rice University Researchers Develop Algorithms Lor 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 & ultra-thin lensless cameras.
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.
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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