Researchers from IIT Madras have collaborated with Rice University in the U.S. and formulated the next miniature imaging technology touted as a Lens-less camera.
This collab had lead to the successful development of new mini lensless cameras. The researchers have developed algorithms for lensless, miniature cameras that have applications in AR/VR, intelligent wearable, robotics, and so much more. Lensless cameras are trumpeted to be the subsequent fate of miniature imaging technology. They deliver imaging capabilities similar to conventional cameras but at much lesser weight, cost and almost flat designed cameras.
What's the major difference?
In traditional cameras, the lens facilitates light to be concentrated onto an imaging sensor, which helps captures a sharp, detailed photograph. But in lensless cameras, the light will be charged by multiple pixels from which the final image has to be developed via particular software.
Back in 2016, Prof. Ashok Veera-Raghavan and his lab assistants have successfully registered in creating a low-cost, low weight and ultra-thin lensless camera.
This newly developed lensless camera was like a thin optical mask placed just in front of the sensor at a distance of roughly 1 mm and tried capturing the picture. Nevertheless, due to the absence of focusing components, the lensless camera captured blurred images limiting their commercial use. The team worked on and formulated an algorithm that potentially reduces the blur in the pictures. The expected algorithm turned out exceptionally and helped reduce the blur in the images and made them equipped to be clearer.
The outcomes and results are thoroughly cited as a paper in the prestigious IEEE International Conference on Computer Vision. An extended version appeared in IEEE Transactions on Pattern Analysis and Machine Intelligence.
According to Dr Kaushik Mitra from IIT-M, the prevailing algorithms produce low-resolution and grainy images, whereas their method significantly improves the whole aspect. He also cited that their research team used Deep Learning and developed a reconstruction algorithm called ‘FlatNet’, which effectively de-blurred images captured by lensless cameras.
While designing newer and better lensless cameras, they thought of using data-driven skills, constructing efficient algorithms for lensless captures, and peeking into crucial applications like endoscopy and intelligent surveillance.
Further, Dr Kaushik Mitra said, “Lensless imaging is a unique technology, and its actual ability is in addressing imaging problems.” He also assured that their team would strive on making new cameras and better efficient algorithms.
This Research was led at IIT Madras by Dr Kaushik Mitra, Assistant Professor, Department of Electrical Engineering. The research team included Mr Salman Siddique Khan, Mr Varun Sundar and Mr Adarsh V.R. from IIT Madras. Prof. Ashok Veeraghavan led the Rice University team, which included Dr Vivek Boominathan and Mr Jasper Tan and was funded by National Science Foundation (NSF) CAREER and NSF EXPEDITIONS, U.S., Neural Engineering System Design (NESD) – Defense Advanced Research Projects Agency (DARPA), U.S., National Institutes of Health (NIH) Grant, U.S., and Qualcomm Innovation Fellowship India 2020.