Studies have shown that camera auto-exposure underestimates the LAI (leaf area index) measured by DHP (digital hemispheric photography) to varying degrees. To address this problem, this paper proposes the use of multi-exposure fusion to reconstruct information from canopy images to compensate for the loss of information caused by overexposure or underexposure of canopy images acquired by the camera in auto-exposure mode. By fusing a series of canopy images with different exposure times from the same canopy layer, the LAI is then calculated using DHP on the fused image. Experimental results show that the method improves the R 2 from 0.698 to 0.837 and reduces the RMSE from 0.87 to 0.37 compared with the automatic exposure mode of the camera, with LAI-2200 measurements as a reference. This method contributes to resolving the problem of underestimating LAI in DHP caused by the automatic exposure mode, thereby improving the accuracy of DHP.