Pre-Processing of Inner CCD Image Stitching of the SDGSAT-1 Satellite

Abstract

Spliced optical satellite cameras suffering from low stitching accuracy are influenced by various factors which can greatly restrict their applications. Most previous studies have focused on the geometric precision of stitched images, which is influenced by the stitching consistency and the relationships between different inner CCD (Charge-Coupled Device) images. Therefore, the stitching accuracy is of great significance in multiple CCD image production. Traditionally, the line-time normalization method has been applied for inner CCD image stitching based on designed line-times with the assumption of uniform sampling during imaging. However, the misalignment of the designed and actual line-time affected by various factors can lead to image distortion. Therefore, this paper investigates the performance of different normalization methods to produce stitched images with higher geometric performance using the actual line-time. First, the geometric distortions caused by misalignments between the designed and actual line-time are analyzed to show the differences in sampling rate and step-points. To overcome the distortions introduced by the fitting error of the designed line-time, three fine normalization methods based on the actual line-time, respectively called scene-based, block-based, and line-based line-time normalization methods, are introduced and compared with the traditional method. The scene-based and block-based line-time normalization methods fit the actual line-time section-by-section, while the line-based method builds the relationships between adjacent inner CCD images line-by-line. Images obtained from the Sustainable Development Goals Satellite 1 (SDGSAT-1) satellite are used for verification of different methods. The performance of the designed line-time normalization method and three fine actual line-time normalization methods is compared; the stitching accuracy can reach about 0.8, 0.56, 0.5, and 0.45 pixels, respectively. The time consumption of these four compared methods is about 5.5 s, 4.9 s, 5.4 s, and 58.9 s, respectively. Therefore, the block-based actual line-time normalization method utilized in practice can provide a good balance between running time and accuracy. In the future, we intend to find a new way to improve the efficiency of line-based line-time normalization methods to produce stitched images with higher geometric consistency and accuracy.