This study proposes an integrated pixel-level reflectance adjustment (IPRA) method using Sentinel-2 MSI as the reference to address radiometric discrepancies in GF-1/6 WFV imagery, particularly caused by sensor decay and geometric distortions. The proposed IPRA method leverages time-series data and a spatial heterogeneity detection mechanism to effectively mitigate geometric distortions. Furthermore, it incorporates a weighted linear regression (WLR) model to weight pixels based on their temporal decay characteristics. The results demonstrate that IPRA outperforms existing methods (i.e., IRMAD, HM, and TRA) in radiometric consistency, yielding smaller radiometric discrepancies relative to Sentinel-2 MSI. Specifically, NAE decreased by 42.9% (from 0.319 to 0.182), RMSE decreased by 37.3% (from 0.051 to 0.032), PSNR improved from 25.906 dB to 30.195 dB, and the SC value approached the ideal value of 1 (from 1.540 to 1.001). In conclusion, the IPRA method provides a robust solution for normalizing GF-1/6 WFV imagery and thus facilitates its cross-sensor applications.