An SoC-FPGA is a large-scale integration (LSI) in which an embedded CPU and FPGA are implemented on a monolithic system. It has higher computational performance than an embedded CPU alone, greater flexibility than an FPGA alone, and can be much smaller than a computer. In addition, selecting reconstruction algorithms that should be implemented as computational circuits is important for designing computers dedicated to single-pixel imaging. FPGAs have higher computational performance but limited hardware resources. They are not good at complex calculations such as division and square root. Optimization methods and deep learning in the algorithm can obtain high-quality reconstruction in single-pixel imaging, and optimization methods suffer from computational load due to the iterative approach.
WiMi's SoC-FPGA trial flow: The camera lens forms an image of the target object on the DMD. The image of the target object is modulated by encoding the mask pattern displayed on the DMD. The modulated light is collected by a lens, measured by a single-device detector, and converted to a digital signal. In addition, a dedicated computer reconstructs the image of the target object based on the light intensity. The FPGA part reconstructs the image, while the embedded CPU on WiMi's SoC-FPGA generates the drawing and initializes it on the holographic display.
Object light is formed on the DMD by the camera lens. A coded mask pattern is displayed on the DMD, modulating the object light. The modulated light is collected by a lens and measured as light intensity by a single-element detector. The obtained light intensity is converted from an analog intensity signal to a digital signal by an analog-to-digital converter. The receiver circuit in the FPGA saves the converted signal in the FPGA internal memory when setting the synchronization signal, which is generated when the DMD is switched to the new coding mask mode. After the receive circuit saves the signal a specified number of times, the reconstruction circuit calculates the target object hologram. Then, the embedded CPU on the SoC-FPGA chip receives the reconstruction result and displays it on a dedicated display panel to realize real-time observation of the holographic image of the target object on a dedicated holographic display panel.
To improve the computational efficiency, the SoC-FPGA uses a ghost imaging correlation algorithm for FPGAs, which has low memory usage and a simple computational form. The algorithm introduces coding mask pattern optimization. This ghost-imaging algorithm improves image quality but has high memory requirements. Specifically, implementing the ghost imaging algorithm requires using two spatially separated beams: a reference beam and an object beam. This imaging method is based on inter-correlation or inter-correlation-like techniques, which allow image reconstruction using a single photon detector.
The basic principle of the algorithm is to perform a correlation measurement between two spatially separated beams and then use a computer algorithm to reconstruct the target image. For example, the reference beam passes through a random interference device that produces random light intensity patterns. These light intensity patterns are transmitted to the object beam, and a single-photon detector detects them after passing through the object. The light intensity values measured by the single-photon detector are recorded and correlated with the light intensity patterns of the reference beam. The information about the target image can be obtained by averaging the multiple inter-correlation measurements.
The ghost imaging algorithm has unique advantages in imaging, such as the ability to achieve three-dimensional holographic imaging without an objective lens, suitability for imaging at low light levels, and suitability for various imaging modes, such as transmission and reflection imaging.
WiMi's SoC-FPGA, a dedicated computer system-on-chip for real-time single-pixel holographic imaging, can achieve higher image quality than conventional holographic imaging technologies. The size, image quality, and speed can be improved for real-time holographic imaging through SoC-FPGA integrated structure and algorithm optimization. And because SoC-FPGAs dedicated to real-time single-pixel holographic imaging are very compact compared to typical computer servers, single-pixel imaging can be extended to IoT and outdoor applications. The dedicated specific applications also include implementing topographic satellite surveys, which can be used for object tracking and building automotive navigation IoT systems.
About WIMI Hologram Cloud
WIMI Hologram Cloud, Inc. (NASDAQ: WIMI) is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.
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SOURCE WiMi Hologram Cloud Inc.
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