Video Compression Imaging Technology Based on High-Frequency Encoding

Video Compressive Imaging (VCI) enables low-dimensional detectors to capture high-dimensional data through incoherent encoding. However, traditional pseudo-random coding often exhibits structural sampling that leads to detail loss. While adjusting the sampling rate can balance structured sampling and incoherence, the reconstruction quality remains unsatisfactory. To overcome this limitation, we propose a high-frequency coding method that mitigates the structural problems of pseudo-random coding by reducing low-frequency components. Simulation results show that this method significantly improves image detail reconstruction, with an average peak signal-to-noise ratio (PSNR) increase of 1.6% across various sampling rates. At a 20% sampling rate, the PSNR improvement reaches around 6%. Furthermore, the method integrates easily into existing VCI systems, offering substantial improvements in image reconstruction quality and reliability compared to pseudo-random coding.