Sinusoidal ghost imaging

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.

Adaptive differential correspondence imaging based on sorting technique

“…[9][10][11][12] In recent years, many improved GI schemes have been developed, including iterative GI, 13 differential GI (DGI), 14 normalized GI (NGI) 15 and others. [16][17][18][19][20] In GI, DGI or NGI schemes, one has to conduct large amounts of correlation calculations between the bucket detector signals and the corresponding reference detector signals. [1][2][3][4][5][13][14][15][16][17][18][19] This procedure is very time consuming, especially in the high quality GI cases, where the number of measurements is extremely large.…”

“…[16][17][18][19][20] In GI, DGI or NGI schemes, one has to conduct large amounts of correlation calculations between the bucket detector signals and the corresponding reference detector signals. [1][2][3][4][5][13][14][15][16][17][18][19] This procedure is very time consuming, especially in the high quality GI cases, where the number of measurements is extremely large. Although the number of measurements can be greatly reduced by compressive sensing (CS) technique, 21,22 the complicated calculations and the requirements imposed on the hardware limit the application of CS.…”

Imaging around corners with single-pixel detector by computational ghost imaging

“…The need for the beam splitter and camera is removed in CGI, which helps GI system become simpler and more applicable. The practical applications of CGI are developed by more and more groups [25][26][27][28][29][30][31][32][33][34]. The speed and quality of imaging have both been improved, such as the real-time video with the single-pixel detectors [31] and the improvement of the signal-to-noise ratio for different systems [32,33].…”

Speckle-Shifting Ghost Imaging

“…(a) Various computational methods focused on improving the imaging quality of GI, e.g. (1) Differential ghost imaging [15], (2) compressive ghost imaging [16], (3) pseudoinverse ghost imaging [17,18], (4) iterative ghost imaging [19,20], sinusoidal ghost imaging [21] and adaptive computational ghost imaging [22]. However, there exists limitation for heavily absorbing objects or they are computationally complex and expensive, and thus difficult for practical applications.…”