Remote sensing of light use efficiency (LUE) is a prerequisite for a timely evaluation of vegetation primary productivity at regional scale. With a potential in detecting the leaf de-epoxidation state of the xanthophyll cycle for heat dissipation, the photochemical reflectance index (PRI) has been demonstrated as a proxy of LUE for various plant functional types at leaf, canopy and ecosystem scales. However, increasing evidence shows that the operational application of PRI using remote sensing data is confounded by canopy structural effects, e.g., the presence of shadows in remote sensing pixels and directional effects associated with changes in illumination and viewing angles. The most important variable that controls the structural associated characteristics is the leaf area index (LAI), which is a major determinant of the absorbed photosynthetic active radiation (APAR) by a canopy. Using ground measured PRI and LUE over three growing seasons on winter wheat in China during 2005-2007, we found that canopy LAI overall explained 66% (p < 0.001) variance of PRI, indicating the essential of removing influences of external structural factors on PRI. Suggested by this, we defined the structural-related signal in PRI (sPRI) as a function of LAI and consequently, the residual PRI (rPRI = PRI-sPRI) would be independent on canopy structural characteristics. Our results showed that a mixed non-linear model using rPRI and variety and sampling time as fixed and random effects, respectively, had an improved accuracy in the estimation of LUE over PRI with increased coefficients of determination (R-2) for both the overall dataset and data of each year. These findings support the structural dependence of PRI and provide a solution for the removal of the structural signal. Further analysis is needed for the application of our approach in other ecosystems that have more complicate canopy structural characteristics than herbaceous monocultures.