This letter introduces a coding aperture design framework for data sampling of CUP-VISAR system in laser inertial confinement fusion (ICF) research. It enhances shock wave velocity fringe reconstruction through feature fusion with a convolutional variational auto-encoder (CVAE) network. Simulation and experimental results indicate that, compared to random coding aperture, the proposed coding matrices exhibit superior reconstruction quality, achieving more accurate fringe pattern reconstruction and resolving coding information aliasing. In experiments, the system SNR and reconstruction quality can be improved by increasing the light transmittance of the encoding matrix. This framework aids in diagnosing ICF in challenging experiment settings.