# Pre-Processing of Inner CCD Image Stitching of the SDGSAT-1 Satellite
## 5 Discussion and Conclusions
 } \\ \hline Image Data 1 & Y & 0.55 & 0.18 & 0.21 & 0.18 \\  & P & 0.55 & 0.43 & 0.45 & 0.56 \\  & P & 0.84 & 0.49 & 0.53 & 0.55 \\ \hline Image Data 2 & X & 0.66 & 0.18 & 0.18 & 0.49 \\  & Y & 0.47 & 0.42 & 0.42 & 0.32 \\  & P & 0.83 & 0.48 & 0.48 & 0.62 development of the pseudo-rigorous model is composed of the projection and reprojection of image-space coordinates between the inner CCD images and the stitched images, which consumes a great deal of time and resources; (2) calibration of internal and external parameters needs to be performed periodically and is based on ground control information, which is hard to obtain; and (3) the performance of the stitched images is determined by the accuracy of external DEMs, as the elevation introduces extra errors during projection and reprojection. Aiming at finding a more efficient method for the production of stitched images with less geometric distortion and higher accuracy, this paper investigates the geometric performance of line-time normalization methods based on the actual line-time. By eliminating the difference between the designed and actual line-times, three line-time normalization methods based on the actual line-time are introduced for fine normalization of adjacent inner CCD images. The development of the scene-based and block-based line-time normalization method is similar to the traditional line-time normalization method. Datasets are divided into segments according to large step-points of the actual line-time, and the sampling intervals are treated as a constant during the normalization. The actual line-time is rather unstable, and the fitting process leads to discrepancies between inner CCD images. Therefore, the line-based actual line-time normalization method is introduced for fine rectification of inner CCD images line by line. We analyzed experimental results using multiple images obtained from the SDGSAT-1 satellite with various coverage. The results indicate that the line-based line-time normalization method achieves the best stitching accuracy, however, the time consumption is greatly increased due to high computational complexity. The block-based actual line-time normalization method can achieve similar accuracy compared to the line-based method with a much lower execution time. Therefore, in practice the block-based line-time normalization method is able to achieve a good balance between accuracy and time. Compared with traditional methods, the actual line-time normalization methods investigated here can avoid geometric distortions caused by misalignment between adjacent inner CCD images. Furthermore, these actual line-time normalization methods can avoid the projection and reprojection of image-space coordinates, greatly simplifying the stitching process. Though the stitching accuracy of the line-based line-time normalization method is the highest, in the follow-up research the efficiency of this method needs to be further analyzed and improved in terms of computational complexity. Conceptualization, N.J., F.W., J.Z. and H.Y. ; Data curation, N.J. and J.Z. and B.C. ; Formal analysis, N.J. and F.W. ; Funding acquisition, F.W. and H.Y. ; Investigation, N.J., B.C. and J.Z. ; Methodology, N.J. and F.W. ; Project administration, N.J., F.W., B.C. and H.Y. ; Resources, F.W. and B.C. ; Writing--original draft, N.J. and J.Z. ; Writing--review and editing, N.J., F.W. and H.Y. All authors have read and agreed to the published version of the manuscript. This research was funded by the From 0 to 1 Original Innovative Project of the Chinese Academy of Sciences Frontier Science Research Program under Grant No. ZDBS-LY-JSC036, by the National Natural Science Foundation of China under Grant No. 61901439, and by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No. XDA19010401. Not applicable. The authors declare no conflict of interest.