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Alignment of Similarity-Transformed Images Based on Fourier--Mellin Transform Using Auxiliary Function Method — arXiv:2608.11565

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.11565
License (as archived): CC0-1.0
Archived: 2026-10-19T05:49:48.294Z
SHA-256 of the archived text: 8e74df5e5c200cf92346973cbf375a2067a57966b359ab8a541983029d071ef9
Stable URL of this page: https://metraipolis.com/documento/dc_87403ed682bb

How to cite

Alignment of Similarity-Transformed Images Based on Fourier--Mellin Transform Using Auxiliary Function Method — arXiv:2608.11565 — arXiv (en), https://arxiv.org/abs/2608.11565 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_87403ed682bb (Metraipolis archive dc_87403ed682bb, sha256 8e74df5e5c200cf92346973cbf375a2067a57966b359ab8a541983029d071ef9)

BibTeX

@misc{dc87403ed682bb,
  title = {Alignment of Similarity-Transformed Images Based on Fourier--Mellin Transform Using Auxiliary Function Method — arXiv:2608.11565},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.11565},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_87403ed682bb; sha256 8e74df5e5c200cf92346973cbf375a2067a57966b359ab8a541983029d071ef9},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.11565. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

This paper proposes an algorithm for estimating the similarity transformation, namely translation, scale, and rotation, between two images with subpixel accuracy. Image registration is a fundamental technique for aligning images acquired under different viewpoints and imaging conditions, and a representative approach based on maximizing discrete cross-correlation is the Fourier--Mellin registration. However, the Fourier--Mellin approach often fails to achieve sufficient alignment accuracy when subpixel-level estimation is required. The proposed method integrates (i) scale-and-rotation estimation from the Fourier magnitude spectrum in a log-polar representation and (ii) maximization of phase-only correlation based on the auxiliary function method. This integration enables a two-stage estimation procedure: it first estimates scale and rotation without being affected by translation, and then estimates translation with subpixel precision in the spatial domain using the corrected image pair. A simulation experiment on image pairs subjected to random similarity transformations demonstrates that the proposed method reduces estimation errors in scale, rotation, and translation compared with Fourier--Mellin-based registration methods using discrete cross-correlation.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-08-13 in cs.CV).
Categorie arXiv: Image and Video Processing (eess.IV) ; Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2608.11565 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-19T05:42:25.938Z dalla pagina https://arxiv.org/catchup/cs.CV/2026-08-13?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).