The characteristic parameters of light response can indicate the process of photosynthesis, capacity of photosynthesis, and response of adversity stress in crops. In order to explore the feasibility of using cellphone photos to predict the light response characteristic parameters of maize, canopy images at the big flare stage of the drip irrigation maize under different nitrogen levels were obtained by the selfdeveloped portable image acquisition device. Feature parameters were extracted from the canopy image, and the photosynthetic physiological characteristics parameters were calculated, such as apparent quantum efficiency (α), dark respiration rate (Rd), light compensation point (LCP) and maximum net photosynthesis rate (Pnmax). A normalized canopy cover factor (CC) was highly correlated with the light response characteristic parameters, as an independent variable was used to predict these parameters. The optimal model was selected according to the model evaluation indicators such as R2, RMSE and nRMSE. The results showed that the optimal model of CC and α was the rational function model, the optimal model of Pnmax was the power function model, the optimal model of LCP was the exponential function model and the optimal model of Rd was the quadratic polynomial model. The R2 values of each model were greater than 0.876, the values of RMSE were between 0.002μmol/(m2·s) and 3.673μmol/(m2·s), and the nRMSE was no more than 9.071%. Meanwhile, the R2 values of each model validation set were greater than 0.833, the RMSE values were less than 5.989μmol/(m2·s), and the nRMSE values were no more than 9.659%. Combining the digital image feature parameters with the maize light response curve characteristic parameters method, it was recommended to quickly acquire characteristic parameters of maize light response curve, which provided a theoretical basis for the light response.