Illumination compensation and normalization using low-rank decomposition of multispectral images in dermatology
Duliu A, Brosig R, Ognawala S, Lasser T, Ziai M, Navab N (2015)
Publication Type: Conference contribution
Publication year: 2015
Journal
Publisher: Springer Verlag
Book Volume: 9123
Pages Range: 613-625
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Isle of Skye, GBR
DOI: 10.1007/978-3-319-19992-4_48
Abstract
When attempting to recover the surface color from an image, modelling the illumination contribution per-pixel is essential. In this work we present a novel approach for illumination compensation using multispectral image data. This is done by means of a low-rank decomposition of representative spectral bands with prior knowledge of the reflectance spectra of the imaged surface. Experimental results on synthetic data, as well as on images of real lesions acquired at the university clinic, show that the proposed method significantly improves the contrast between the lesion and the background.
Involved external institutions
Germany (DE)How to cite
APA:
Duliu, A., Brosig, R., Ognawala, S., Lasser, T., Ziai, M., & Navab, N. (2015). Illumination compensation and normalization using low-rank decomposition of multispectral images in dermatology. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 613-625). Isle of Skye, GBR: Springer Verlag.
MLA:
Duliu, Alexandru, et al. "Illumination compensation and normalization using low-rank decomposition of multispectral images in dermatology." Proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, Isle of Skye, GBR Springer Verlag, 2015. 613-625.
BibTeX: Download