Coded Illumination And Multiplexing For Lensless Imaging
M. Salman Asif, Yucheng Zhang, Rongjia Zheng
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Mask-based lensless cameras offer an alternative option to conventional cameras. Compared to conventional cameras, lensless cameras can be extremely thin, flexible, and light-weight. Despite these advantages, the quality of images recovered from the lensless cameras is often poor because of the ill-conditioning of the underlying linear system. In this paper, we propose a new method to address the problem of ill-conditioning by combining coded illumination patterns with the mask-based lensless imaging. We assume that the object is illuminated with multiple binary patterns and the camera acquires a sequence of images for different illumination patterns. We propose a low-complexity, recursive algorithm that avoids storing all the images or creating a large system matrix. We present simulation results on standard test images under various extreme conditions and demonstrate that the quality of the image improves significantly with a small number of illumination patterns.