## 4 Discussion  
Using multispectral (MS) bands (G, B, NIR, and RE) as binocular lens pairs (with the fixed red band) in the stereo vision systems, the image-alignment model showed significant differences in performance depending on the spectral band and the range of distances selected for calibration, ranging from 500 mm to 1500 mm. The stereo vision approach, evaluated by reprojection error (expressed in pixels), demonstrated promising accuracy in the calibration set, with total mean errors of approximately 0.013 pixels for all band pairs. The minimum deviation between recognized homologous points in the two scenes of the stereo system, for the calibration of two or more camera lenses, was less than 1 pixel, a value considered robust in these contexts. The effect of distance on error was consistent across all pairwise systems used, with maximum values recorded at the extremes of the distance set. However, the behavior of the error along the X- and Y-axes of the image differed. In particular, the reprojection error along the Y-axis had a noticeable impact on our calibration set, especially for the G and RE band pairs. Compared with the B, RE, and NIR bands, the G band exhibited a higher average error along the Y-axis. In contrast, the RE band showed a more stable and less variable mean trend. The accuracy of the depth (\(Z\)) estimation was directly influenced by the reprojection error, which was conceptually related to the calculated disparity in the 3D coordinates of the images in the set [51]. The higher errors observed at distances greater than 1000 mm were likely due to reduced accuracy in disparity estimation and the challenges of identifying similarities between stereo images at larger distances. Indeed, the larger the error, the lower the accuracy in aligning homologous points between the two scenes acquired from the same viewpoint. As expected, the G and RE bands exhibited opposite behaviors in estimation accuracy, with minimum and maximum errors of 18% and 5% for the G band and 23% and 10% for the RE band, respectively. This highlighted the greater stability of the RE band compared with the G band in estimates. The best results were obtained at smaller distances (800 mm) in the validation set, while a peak in error was observed at the intermediate distance of 1000 mm. These results suggested clear directions for optimizing stereo calibration, which could involve exploring more robust metrics to mitigate the impact of reprojection errors, particularly along the Y-axis, and improve overall system performance. In the image alignment model, the tested methods (CB, FT, and RG) showed good results in terms of correlation with the experimental data, as highlighted by adjusted R\({}^{2}\) values around 0.99, suggesting strong fitting capability. This indicated that the applied models were able to accurately capture the spatial relationships between the multispectral bands, enabling proper alignment of the images. Analysis of the residual offset, expressed as the error along the X (Xerr) and Y (Yerr) axes, allowed the assessment of the effect of the different bands on the quality of the alignment. In this regard, errors along the X-axis had a greater impact on the overall quality of the models. The G and RE bands were found to be strongly uncorrelated with the experimental model (with R\({}^{2}\) values of \(-\)0.0159 and \(-\)0.2168, respectively) along the X-axis, indicating that alignment along this direction was not optimal for these bands. These results suggested that the model had difficulty in representing accurately the spatial relationship for this pair of bands. Despite this, the residual offset errors along the X- and Y-axes were found to be in the range of \(\pm\)2 to \(\pm\)3 pixels, suggesting that the spatial alignment predicted by the model was still satisfactory for all methods tested.