Efficient Feature-based Image Registration by Mapping Sparsified Surfaces
This work addresses efficiency bottlenecks in image registration for industries like computer graphics and film production, though it appears incremental as it builds on existing surface registration methods.
The paper tackles the problem of slow image registration for high-resolution images and videos by proposing a new triangulation-based representation method, achieving significant reductions in computational time while maintaining registration accuracy compared to conventional grid-based approaches.
With the advancement in the digital camera technology, the use of high resolution images and videos has been widespread in the modern society. In particular, image and video frame registration is frequently applied in computer graphics and film production. However, conventional registration approaches usually require long computational time for high resolution images and video frames. This hinders the application of the registration approaches in the modern industries. In this work, we first propose a new image representation method to accelerate the registration process by triangulating the images effectively. For each high resolution image or video frame, we compute an optimal coarse triangulation which captures the important features of the image. Then, we apply a surface registration algorithm to obtain a registration map which is used to compute the registration of the high resolution image. Experimental results suggest that our overall algorithm is efficient and capable to achieve a high compression rate while the accuracy of the registration is well retained when compared with the conventional grid-based approach. Also, the computational time of the registration is significantly reduced using our triangulation-based approach.