This research presents a high-resolution non-line-of-sight (NLOS) imaging system based on liquid crystal planar optical elements (LC-POEs). The system enables a large field-of-view and high-resolution imaging by integrating an angle magnification system with a confocal NLOS imaging setup. The LC-POEs, which offer advantages such as high efficiency, lightweight, low cost, and ease of processing, are used to achieve angle magnification and expand the scanning area. A sparse scanning method is introduced to reduce data acquisition time by leveraging spatial correlation between adjacent scanning positions, resulting in a >20% reduction in data acquisition time while maintaining the same resolution. The system uses a cascaded LC-POE configuration to create a miniature telescope, achieving efficient, wide-angle, and high-precision beam deflection. The LC-POEs are designed to manipulate the geometric phase of light, enabling precise control over the beam direction. Experimental results demonstrate that the system significantly improves image quality and resolution compared to traditional NLOS imaging systems. The reconstructed images show a 5 dB increase in peak signal-to-noise ratio (PSNR) and a 15% reduction in root mean square error (RMSE) compared to the angle-constrained system. The system also incorporates a sparse scanning approach based on spatial correlation, which reduces the number of sampling points while maintaining high spatial resolution. This method allows for a 26% reduction in scanning time and a 5 dB increase in PSNR. The results show that the system can effectively reconstruct complex three-dimensional objects with high accuracy and resolution. The study highlights the potential of LC-POEs in NLOS imaging, offering a compact, efficient, and high-resolution solution for imaging hidden objects. The integration of sparse scanning with expanded scanning areas provides a novel approach to NLOS imaging, enhancing the capabilities beyond traditional methods. The research contributes to the development of real-time NLOS imaging and opens new possibilities for applications in security monitoring, search and rescue, and autonomous driving.This research presents a high-resolution non-line-of-sight (NLOS) imaging system based on liquid crystal planar optical elements (LC-POEs). The system enables a large field-of-view and high-resolution imaging by integrating an angle magnification system with a confocal NLOS imaging setup. The LC-POEs, which offer advantages such as high efficiency, lightweight, low cost, and ease of processing, are used to achieve angle magnification and expand the scanning area. A sparse scanning method is introduced to reduce data acquisition time by leveraging spatial correlation between adjacent scanning positions, resulting in a >20% reduction in data acquisition time while maintaining the same resolution. The system uses a cascaded LC-POE configuration to create a miniature telescope, achieving efficient, wide-angle, and high-precision beam deflection. The LC-POEs are designed to manipulate the geometric phase of light, enabling precise control over the beam direction. Experimental results demonstrate that the system significantly improves image quality and resolution compared to traditional NLOS imaging systems. The reconstructed images show a 5 dB increase in peak signal-to-noise ratio (PSNR) and a 15% reduction in root mean square error (RMSE) compared to the angle-constrained system. The system also incorporates a sparse scanning approach based on spatial correlation, which reduces the number of sampling points while maintaining high spatial resolution. This method allows for a 26% reduction in scanning time and a 5 dB increase in PSNR. The results show that the system can effectively reconstruct complex three-dimensional objects with high accuracy and resolution. The study highlights the potential of LC-POEs in NLOS imaging, offering a compact, efficient, and high-resolution solution for imaging hidden objects. The integration of sparse scanning with expanded scanning areas provides a novel approach to NLOS imaging, enhancing the capabilities beyond traditional methods. The research contributes to the development of real-time NLOS imaging and opens new possibilities for applications in security monitoring, search and rescue, and autonomous driving.