In this following section we propose to use the homography and rectification for image inpainting with multiple images.
In this section we discuss how to apply homography and rectification for image inpainting with multiple images.
This paper describes a methodology based on state-of-the-art tools (for example, that apply classical PIV/PTV analysis) resulting in large-scale surface-flow characterization according to the first operational version of the RIVeR (Rectification of Image Velocity Results).
Image rectification is essential (i) to remove the image distortion induced by the camera lens (especially in the borders of the image) and (ii) to align the images acquired by two different points of view in order to subsequently apply the epipolar geometry during the feature-matching task [21].
Theoretically, for ortho-rectification of images, the DEM data should be obtained at the same time as that of the high-resolution images and make sure that their spatial resolutions are consistent.
However, in actual ortho-rectification of images, their spatial resolutions are inconsistent.
For the ortho-rectification of images in this paper, two kinds of DEM data can be used.
It uses low cost and portable scale bars, specially designed for thermal imaging, and processing software based on single image rectification.
Image rectification is an important component of stereo vision process.
The established invariants in the paper have other potential applications such as camera calibration, image rectification, structure reconstruction, image matching, and object recognition.
