A Subpixel Registration Algorithm for Low PSNR Images
Song Feng, Linhua Deng, Guofeng Shu, Feng Wang, Hui Deng, Kaifan Ji

TL;DR
This paper introduces a fast, high-accuracy subpixel registration algorithm for low PSNR images using centroid measurement on the cross correlation surface, offering comparable accuracy with improved speed.
Contribution
The paper proposes a novel subpixel registration method based on centroid measurement, which is faster and maintains accuracy for low PSNR images compared to existing techniques.
Findings
Accuracy comparable to existing methods
Higher processing speed
Effective on synthetic and real images
Abstract
This paper presents a fast algorithm for obtaining high-accuracy subpixel translation of low PSNR images. Instead of locating the maximum point on the upsampled images or fitting the peak of correlation surface, the proposed algorithm is based on the measurement of centroid on the cross correlation surface by Modified Moment method. Synthetic images, real solar images and standard testing images with white Gaussian noise added were tested, and the results show that the accuracies of our algorithm are comparable with other subpixel registration techniques and the processing speed is higher. The drawback is also discussed at the end of this paper.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
