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Single-pixel imaging (SPI), which is generally based on computational imaging, has the advantages of a wide bandwidth and the ability to image objects beyond the visual field. However, the major challenge in developing SPI is the large number of illumination patterns that are required. Unlike traditional SPI that relies on random measurement patterns, the SPI method proposed in this letter involves a two-step phase shift that reduces greatly the required number of illumination patterns. Theoretical analysis shows that 6724 illumination patterns are required to reconstruct a 128 × 128-pixel image whose peak signal-to-noise ratio exceeds 30, and these can be projected in 0.3362 s with a digital micromirror device working at full speed. Compared to SPI with a four-step phase shift, half the number of illumination patterns are required. Verification experiments show that the reconstructed images can be obtained even at a sampling ratio of 20%. The proposed SPI with a two-step phase shift is an effective means of requiring fewer illumination patterns and has great potential in dynamic detection. [ABSTRACT FROM AUTHOR]

Single-pixel imaging technology is popular with invisible wavelengths and low light environments. However, the time-consuming steps hindered the development of single-pixel imaging technology. To improve imaging efficiency, a high-efficiency one-step single-pixel imaging method based on the discrete Hartley transform is proposed. The proposed method does not require a large number of fringe patterns and only requires a real-number calculation. The number of fringe patterns required for the proposed method is only half of that required for the four-step phase-shift Fourier method at the same sampling rate. Although a one-step method, it also uses the idea of differential measurements and adds upsampling processing strategies, which simultaneously improve the signal-to-noise ratio of the recovered image. The simulation shows that the peak signal-to-noise ratio and structural similarity index of the recovered target scene exceed 20 dB and 80%, respectively, when the sampling rate is 30%. Only 20 164 patterns are needed to reconstruct a (256 × 256)-pixel image. After defocusing the gray stripe pattern into a binary pattern, it only takes milliseconds to project these patterns into the target. It can be seen that the experimental results of the proposed method are significantly better than those of the two-step phase-shift method under dramatical noise interference. With the rapid development of advanced equipment, this method will represent significant progress in the real-time reconstruction of single-pixel imaging. [ABSTRACT FROM AUTHOR]

The security of liveness detection in face recognition is a crucial issue, but many attacks can spoof current face feature techniques. To enhance the security of liveness detection, a method is proposed to extract human physiological components from the object and classify the properties. The proposed method, different from traditional camera-based methods that require specific movement of the human face, separates the heart rate (HR) components from the computational ghost imaging (CGI) signal and achieves liveness detection by capturing only one image rather than image sequences. The correct rate reaches 96.0% against picture attacks and mask attacks. The average error is only 3.57% compared to commercial contact HR measuring devices. Meanwhile, this method is found resolution-independent and can work in low-resolution conditions, which is experimentally verified at a resolution of 32 × 32 pixels. This method can enhance the security of liveness detection and provide a fresh framework for physiological measurements. [ABSTRACT FROM AUTHOR]