This paper investigates the effect of the linearization of camera JPG data on the accuracy of spectral reflectance reconstruction based on weighted polynomial regression algorithm and demonstrates whether the JPG data needs to be linearized in the weighted polynomial regression algorithm. This method was trained using the X-Rite Digital ColorChecker Semi Gloss (SG) chart including 140 color and grey patches and tested using the GretagMacbeth ColorChecker chart including 24 color and grey patches, and self-made 44 printed and 48 textile samples. Comparison results based on real camera data have shown that the weighted polynomial regression method with the original JPG data outperformed the weighted polynomial regression method with the linearized JPG data measured in terms of CIEDE2000 color difference and root-mean-square error. Based on the results of this study, linearization of the JPG data does not improve the reconstruction accuracy for reconstructing the reflectance using the weighted polynomial regression method. Without JPG data linearization, higher spectral reconstruction accuracy can also be obtained. The weighted three order polynomial regression method performed the best with original JPG data.