Abstract

We introduce sinusoidal ghost imaging (SGI), which uses 2D orthogonal sinusoidal patterns instead of random patterns in “computational ghost imaging” (CGI). Simulations and experiments are performed. In comparison with the“differential ghost imaging” algorithm that was used to improve the SNR of ghost imaging, results of SGI show about 3 orders of magnitude higher SNR, which can be reconstructed even with a much smaller number of patterns. More importantly, based on the results, SGI provides the great opportunity to generate innate processed images by predefined selection of patterns. This can speed up detection process considerably and paves the way for real applications.

© 2015 Optical Society of America

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