Sensor Correction Method Based on Image Space Consistency for Planar Array Sensors of Optical Satellite

To increase the observation performance of optical remote sensing satellites (ORSSs), onboard camera systems usually perform multislice and multiband imaging. The resulting multiband or multislice subimages require correction into an aligned and stitched complete image, to provide users with standard image products. In a linear array sensor, multiband and multislice sensor correction processing is achieved by mapping subimages on the same virtual linear array based on the determined geometric parameters and the principle of object space consistency. However, a planar array sensor has the same geometric parameters outside the camera; therefore, object space consistency is essentially equivalent to image space consistency, which simplifies coordinate mapping calculations. In this study, we developed a novel sensor correction method based on image space consistency for planar array sensors and combined it with a method to determine the relative geometric parameters between bands. The internal geometric parameters of multiple bands were determined under connection constraints between bands established by consistent image space pointing. Next, the coordinate mapping model between the virtual image point and physical subimage point was established, and the angular resolution was introduced for coordinate solving. Based on strict geometric correspondence between the subimages and virtual images, the whole image with interband registration and interslice stitching was generated from the subimages. We experimentally verified the accuracy and effectiveness of our method using real multiband and simulated multislice plane array sensor images from GF-4 satellites. The corrected whole image showed satisfactory interband registration accuracy and internal geometric accuracy.