Thin-Plate-Spline-Based Registration for Correcting Local Nonlinear Deformation of Bidirectional Whisk-Broom Images

High-precision geometric registration has been widely used in remote-sensing applications, such as image fusion. In practice, it is found that the geometric deformation (GD) of the bidirectional whisk-broom images, namely forward- and backward-scanning images, is not evenly distributed. Additionally, the deformation in some special areas exhibits significant nonlinear characteristics, which ultimately makes the traditional linear homography matrix inoperative in describing the GD of the whole image. Meanwhile, it is difficult to establish an elastic deformation model for the whole image due to the large swath and complex GD. To solve the problems above, we proposed a thin-plate-spline-based registration method for correcting the nonlinear deformation of large-size bidirectional whisk-broom images through scene classification. First, a classification method based on histogram Gaussian distribution fitting is proposed to divide the image into sea and land blocks of the same size. And the adjacent blocks must have overlapping areas. Second, the thin-plate-spline transformation is carried out to correct the local nonlinear deformation of the land blocks. Finally, the registered blocks are stitched by a gradual image fusion method to obtain the fully registered images. Our proposed method can correct the local nonlinear GD of bidirectional whisk-broom images of sustainable development science satellite 1 thermal infrared spectrometer (TIS), and the registration accuracy is better than 0.3 pixels, which is of great significance for the practical application of TIS thermal infrared image.