A team of researchers from the Indian Institute of Technology, Madras and US-based Rice University have together developed algorithms for lensless and miniature cameras.

The lensless cameras have numerous vision applications in sectors including Augmented Reality, Virtual Reality, security, smart wearables and robotics where cost, form-factor, and weight become major constraints, IITM said in a release on Thursday.

"IIT Madras and Rice University researchers have developed a deep learning algorithm for producing photo-realistic images from the blurred lensless capture", the release said.

While the IITM team was led by Assistant Professor Kaushik Mitra of the Department of Electrical Engineering, the research by Rice University was led by Professor Ashok Veeraraghavan.

"Existing algorithms to deblur images based on traditional optimisation schemes yield low-resolution 'noisy images'. Our research team used 'Deep Learning' to develop a reconstruction algorithm called FlatNet for lensless cameras resulting in significant improvement", Mitra said.

"FlatNet was tested on various real and challenging scenarios and was found to be effective in de-blurring images captured by the lensless camera", he added.

The research team was funded by National Science Foundation (NSF) CAREER and NSF Expeditions, United States Neural Engineering System Design - Defense Advanced Research Projects Agency, United States, among others, the release added.