Computational Ghost Imaging Based on Orthogonal Sinusoidal Speckle

A computational ghost imaging method based on orthogonal sinusoidal speckle was proposed herein to solve the problem of low signal-to-noise ratio caused by the non-orthogonality of random speckle distributions. This method combines the orthogonal property of a matrix, superimposes two orthogonal oblique sinusoidal distribution patterns, and constructs an orthogonal sinusoidal speckle field to image unknown targets by adjusting the tippet-frequency limit. Experimental results and numerical simulations show that the ghost image quality obtained by the proposed method has significantly improved as compared with that obtained by the computational ghost imaging based on the Gaussian speckle pattern, and the peak of signal-to-noise ratio is increased by 4 dB-7 dB. Furthermore, the structural similarity is improved by 280%.