In recent years, the acquisition of high-resolution multi-spectral images by unmanned aerial vehicles (UAV) for quantitative remote sensing research has attracted more and more attention, and radiometric calibration is the premise and key to the quantification of remote sensing information. The traditional empirical linear method independently calibrates each channel, ignoring the correlation between spectral bands. However, the correlation between spectral bands is very valuable information, which becomes more prominent as the number of spectral channels increases. Based on the empirical linear method, this paper introduces the constraint condition of spectral angle, and makes full use of the information of each band for radiometric calibration. The results show that, compared with the empirical linear method, the proposed method can effectively improve the accuracy of radiometric calibration, with the improvement range of Mean Relative Percent Error (MRPE) being more than 3% in the range of visible band and within 1% in the range of near-infrared band. Besides, the method has great advantages in agricultural remote sensing quantitative inversion.