Reversão anaglífica baseada em método rápido
Resumo
3D formats are still relevant due to their ability to convey depth through stereoscopic techniques. Among these, the anaglyph method stands out for its simplicity and low cost, encoding stereo pairs into a single image. Despite its advantages in compression and transmission, anaglyph encoding discards significant information, making its reversion complex. Reversing anaglyphs enables legacy content recovery and broader compatibility with various stereoscopic visualization methods. This work proposes an efficient approach to anaglyph reversion by exploring Block Matching algorithm, commonly used in video coding. Unlike traditional methods relying on pixel descriptors and global optimizations—often computationally expensive—our technique aims to handle radiometric differences between stereo views while maintaining high image quality and improved performance. Experimental results demonstrate the potential of this method as an alternative to existing solutions.
Palavras-chave:
Anaglyph reversion, Block matching, Stereo images
Referências
A. L. D. Costa. 2021. Reversão anaglífica - um novo método baseado em cálculo de correspondências robusto a diferenças radiométricas. Dissertação (Mestrado em Ciências – Ciências de Computação e Matemática Computacional). ICMC/USP, São Carlos – SP.
M. Dasygenis and P. Michailidis. 2014. Evaluating modern parallelization techniques on block matching algorithms. In Proc. of the 18th Panhellenic Conference on Informatics. DOI: 10.1145/2645791.2645839
B. Goldstein. 2013. Sensation and Perception (8 ed.). Wadsworth Cengage Learning, Belmont, CA. 1–490 pages.
R. C. Gonzalez and R. E. Woods. 2006. Digital Image Processing (3rd Edition). Prentice-Hall, Inc., USA, Chapter 10.
A. Joulin and S. B. Kang. 2013. Recovering Stereo Pairs from Anaglyphs. In 2013 IEEE Conf. on Computer Vision and Pattern Recognition. 289–296. DOI: 10.1109/CVPR.2013.44
J. Konrad. 2005. 3.10 - Motion Detection and Estimation. In Handbook of Image and Video Processing (Second Edition) (second edition ed.), AL BOVIK (Ed.). Academic Press, Burlington, 253–274. DOI: 10.1016/B978-012119792-6/50079-6
L. F. Kunze, R. Goularte, and E. P. M. Sousa. 2020. SIRA - An efficient method for retrieving stereo images from anaglyphs. Signal Process. Image Commun. 85, 115866 (July 2020), 115866.
A. Levin, D. Lischinski, and Y. Weiss. 2004. Colorization using Optimization. ACM Transact. on Graphics 23 (06 2004). DOI: 10.1145/1015706.1015780
Bernard Mendiburu. 2009. 3D Movie Making: Stereoscopic Digital Cinema from Script to Screen. Focal Press.
F. M. Rodrigues, J. K. Yugoshi, and R. Goularte. 2016. HaaRGlyph: A New Method for Anaglyphic Reversion in Stereoscopic Videos. In Proc. of the 22nd Brazilian Symposium on Multimedia and the Web. DOI: 10.1145/2976796.2976864
D. Scharstein and R. Szeliski. 2002. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. Intern. Journal of Computer Vision 47 (04 2002), 7–42. DOI: 10.1023/A:1014573219977
D. Scharstein and R. Szeliski. 2003. High-accuracy stereo depth maps using structured light. Comput. Vision Pattern Recognit. 1, I–195. DOI: 10.1109/CVPR.2003.1211354
StereoGraphics Corporation. 1997. Stereographics Developers Handbook: Background on Creating Images for CrystalEyes and SimulEyes.
W. Williem, R. Raskar, and I. K. Park. 2015. Depth Map Estimation and Colorization of Anaglyph Images Using Local Color Prior and Reverse Intensity Distribution. In 2015 IEEE Intern. Conf. on Computer Vision (ICCV). 3460–3468. DOI: 10.1109/ICCV.2015.395
Peter Wimmer. [n. d.]. DeAnaglyph. Retrieved July 03, 2025 from [link]
J. K. Yugoshi. 2018. Reversão anaglífica baseada em busca local rápida. Dissertação (Mestrado em Ciências – Ciências de Computação e Matemática Computacional). ICMC/USP, São Carlos – SP.
M. R. U. Zingarelli, L. A. Andrade, and R. Goularte. 2011. Reversing Anaglyph Videos Into Stereo Pairs. In Proceed. of the 17th Brazilian Symposium on Multimedia and the Web. [link]
M. Dasygenis and P. Michailidis. 2014. Evaluating modern parallelization techniques on block matching algorithms. In Proc. of the 18th Panhellenic Conference on Informatics. DOI: 10.1145/2645791.2645839
B. Goldstein. 2013. Sensation and Perception (8 ed.). Wadsworth Cengage Learning, Belmont, CA. 1–490 pages.
R. C. Gonzalez and R. E. Woods. 2006. Digital Image Processing (3rd Edition). Prentice-Hall, Inc., USA, Chapter 10.
A. Joulin and S. B. Kang. 2013. Recovering Stereo Pairs from Anaglyphs. In 2013 IEEE Conf. on Computer Vision and Pattern Recognition. 289–296. DOI: 10.1109/CVPR.2013.44
J. Konrad. 2005. 3.10 - Motion Detection and Estimation. In Handbook of Image and Video Processing (Second Edition) (second edition ed.), AL BOVIK (Ed.). Academic Press, Burlington, 253–274. DOI: 10.1016/B978-012119792-6/50079-6
L. F. Kunze, R. Goularte, and E. P. M. Sousa. 2020. SIRA - An efficient method for retrieving stereo images from anaglyphs. Signal Process. Image Commun. 85, 115866 (July 2020), 115866.
A. Levin, D. Lischinski, and Y. Weiss. 2004. Colorization using Optimization. ACM Transact. on Graphics 23 (06 2004). DOI: 10.1145/1015706.1015780
Bernard Mendiburu. 2009. 3D Movie Making: Stereoscopic Digital Cinema from Script to Screen. Focal Press.
F. M. Rodrigues, J. K. Yugoshi, and R. Goularte. 2016. HaaRGlyph: A New Method for Anaglyphic Reversion in Stereoscopic Videos. In Proc. of the 22nd Brazilian Symposium on Multimedia and the Web. DOI: 10.1145/2976796.2976864
D. Scharstein and R. Szeliski. 2002. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. Intern. Journal of Computer Vision 47 (04 2002), 7–42. DOI: 10.1023/A:1014573219977
D. Scharstein and R. Szeliski. 2003. High-accuracy stereo depth maps using structured light. Comput. Vision Pattern Recognit. 1, I–195. DOI: 10.1109/CVPR.2003.1211354
StereoGraphics Corporation. 1997. Stereographics Developers Handbook: Background on Creating Images for CrystalEyes and SimulEyes.
W. Williem, R. Raskar, and I. K. Park. 2015. Depth Map Estimation and Colorization of Anaglyph Images Using Local Color Prior and Reverse Intensity Distribution. In 2015 IEEE Intern. Conf. on Computer Vision (ICCV). 3460–3468. DOI: 10.1109/ICCV.2015.395
Peter Wimmer. [n. d.]. DeAnaglyph. Retrieved July 03, 2025 from [link]
J. K. Yugoshi. 2018. Reversão anaglífica baseada em busca local rápida. Dissertação (Mestrado em Ciências – Ciências de Computação e Matemática Computacional). ICMC/USP, São Carlos – SP.
M. R. U. Zingarelli, L. A. Andrade, and R. Goularte. 2011. Reversing Anaglyph Videos Into Stereo Pairs. In Proceed. of the 17th Brazilian Symposium on Multimedia and the Web. [link]
Publicado
10/11/2025
Como Citar
MACHADO, Felipe Carneiro; GOULARTE, Rudinei.
Reversão anaglífica baseada em método rápido. In: CONCURSO DE TRABALHOS DE INICIAÇÃO CIENTÍFICA - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 31. , 2025, Rio de Janeiro/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 77-80.
ISSN 2596-1683.
DOI: https://doi.org/10.5753/webmedia_estendido.2025.16347.
