Single-pixel panoramic imaging based on Walsh-Hadamard basis

Abstract Single-pixel panoramic imaging (SPPI) technology, which integrates convex mirrors with computational imaging algorithms, achieves efficient panoramic perception and demonstrates application potential in autonomous driving perception, pipeline inspection and low-altitude related applications. However, its algorithmic efficiency and accuracy still require optimization. This study improves the SPPI system from two aspects: modulation mode and reconstruction algorithm. In terms of modulation, the Walsh-Hadamard (W-H) orthogonal basis structure pattern is introduced, which effectively alleviates the noise sensitivity problem of the random mode in SPPI. In terms of algorithms, this study adapts and optimizes two key approaches for panoramic scenes: the orthogonal algorithm based on two-dimensional (2D) W-H transformation and the 2D compressive sensing (2DCS) algorithm based on the 2D Variational Augmented Lagrange Multiplier (V2DALM). These approaches enable independent asymmetric sampling in the radial and angular dimensions, allowing flexible configuration of sampling resources according to the characteristics of different scenes. The experimental system adopts a passive imaging mode, further enhancing the practicality and adaptability of SPPI. This study provides a scalable theoretical support for single-pixel panoramic perception systems and corresponding SPPI schemes for three typical requirements: high-fidelity imaging, high-speed reconstruction, and speed-fidelity trade-off. Finally, the SPPI performance of the V2DALM algorithm under different modulation patterns has been preliminarily analyzed and discussed.