# Pre-Processing of Inner CCD Image Stitching of the SDGSAT-1 Satellite
## 3 Methodology
### Fine Line-Time Normalization  
The pixel intervals between each scan line are different due to the instability of the satellite platform. Figures 7 and 8 illustrate an example of the line-time difference of the tested image data 1. As shown in Figure 7, the differences between the designed line-time (orange line) and the actual line-time (blue line) are noticeable, especially when there is interference. Figure 7 illustrates the difference between the actual and designed line-times in each scan line. The maximum difference can reach 200 ns, which amounts to a difference of about 1.4%; this is introduced considering that the standard line-time of a scan line is 1440 ns. Figure 8 illustrates the details of the designed line-time (orange line) and the actual line-time (blue line) of the first 500 scan lines of image data 1. The red rectangle rectangles represent the step points of the designed line-time, which is inconsistent with the change in the actual line-time. The step points of the actual and designed line-times are not synchronous; the same conclusion can be drawn from other datasets. Ths is the reason that image-space calibration models based on designed line-time normalization methods suffer from image distortion in sub-CCD image stitching. Furthermore, most object-space based models cannot provide more accurate results if the rigorous sensor model is established based on a designed line-time. Usually, the satellite position and attitude parameters are recorded sparsely. The interpolation of position and attitude introduces fitting errors during the reprojection of image-space pixels. Furthermore, the reprojection process introduces image distortion due to the unstable geolocation error of the satellite platform. Therefore, the object-space inner CCD image stitching method is influenced by various factors in the establishment of a pseudo-rigorous geolocation model. For stitching developed in image-space, the design of mismatched imaging rates leads to results in which the sampling intervals between adjacent scan lines are not the same, which results in local image distortion if not calibrated correctly. As shown in Figure 9, the accumulated time error between the actual and designed line-times is about 0.5 ms for around 10,000 scan lines. Assuming that the average speed of the satellite platform is about 7.6 km/s, the resulting ground difference can reach 4 m. This distortion is consequential for images with very high resolution and cannot be neglected. Considering that the ground resolution for multispectral images obtained from the SDGSAT-1 satellite is 10 m with a swath of 300 km, a mismatched imaging line-time introduces pixel-level distortions in standard image products. It is noteworthy that line-time mismatching is an essential issue in image distortion, significantly compromising the geometric performance and further applications of these products. Figure 6: Illustration of the traditional line-time normalization method: (**a**) inner CCD image before traditional line-time normalization and (**b**) inner CCD image after traditional line-time normalization. Figure 8: Detailed differences between the actual and designed line-times of the first 1000 scan lines of Image Data 1. Figure 7: Time differences between the actual line-time and design line-time: (**a**) comparison between the designed and actual line-time of Image Data 1 and (**b**) time differences between the designed and actual line-time of Image Data 1. Figure 9: Accumulated time error between the actual and designed line-time. In this paper, different fine line-time normalization methods, namely, scene-based, block-based, and line-based line-time normalization methods, are investigated based on the actual line-time. Compared with the results in Figure 6a, Figure 10a illustrates that the sampling distance of the raw data is various in object-space. The actual line-time is recorded in the metafile of each sca nline.