This paper presents a novel approach for spectral illuminant correction in smartphone imaging systems, aiming to improve color accuracy and enhance image quality. The methods introduced include Spectral Super Resolution and Weighted Spectral Color Correction (W-SCC). These techniques leverage the spectral information of both the image and the illuminant to perform effective color correction. Experimental evaluations were conducted using a dataset of 100 synthetic images, whose acquisition is simulated using the transmittance information of a Huawei P50 smartphone camera sensor and an Ambient light Multispectral Sensor (AMS). The results demonstrate the superiority of the proposed methods compared to traditional trichromatic pipelines, achieving significant reductions in colorimetric errors measured in terms of ∆E94 units. The W-SCC technique, in particular, incorporates per-wavelength weight optimization, further enhancing the accuracy of spectral illuminant correction. The presented approaches have valuable applications in various fields, including color analysis, computer vision, and image processing. Future research directions may involve exploring additional optimization techniques and incorporating advanced machine learning algorithms to further advance spectral illuminant correction in smartphone imaging systems.

Buzzelli, M., Tchobanou, M., Schettini, R., Bianco, S. (2023). RGB Illuminant Compensation using Spectral Super-resolution and Weighted Spectral Color Correction. In 31st Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2023 (pp.33-37). Society for Imaging Science and Technology [10.2352/cic.2023.31.1.7].

RGB Illuminant Compensation using Spectral Super-resolution and Weighted Spectral Color Correction

Buzzelli, M;Schettini, R;Bianco, S
2023

Abstract

This paper presents a novel approach for spectral illuminant correction in smartphone imaging systems, aiming to improve color accuracy and enhance image quality. The methods introduced include Spectral Super Resolution and Weighted Spectral Color Correction (W-SCC). These techniques leverage the spectral information of both the image and the illuminant to perform effective color correction. Experimental evaluations were conducted using a dataset of 100 synthetic images, whose acquisition is simulated using the transmittance information of a Huawei P50 smartphone camera sensor and an Ambient light Multispectral Sensor (AMS). The results demonstrate the superiority of the proposed methods compared to traditional trichromatic pipelines, achieving significant reductions in colorimetric errors measured in terms of ∆E94 units. The W-SCC technique, in particular, incorporates per-wavelength weight optimization, further enhancing the accuracy of spectral illuminant correction. The presented approaches have valuable applications in various fields, including color analysis, computer vision, and image processing. Future research directions may involve exploring additional optimization techniques and incorporating advanced machine learning algorithms to further advance spectral illuminant correction in smartphone imaging systems.
slide + paper
illuminant correction, color correction, spectral data, spectral color adaptation transform
English
31st Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2023 - 13 November 2023 through 17 November 2023
2023
31st Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2023
2023
31
1
33
37
https://library.imaging.org/cic/articles/31/1/7
reserved
Buzzelli, M., Tchobanou, M., Schettini, R., Bianco, S. (2023). RGB Illuminant Compensation using Spectral Super-resolution and Weighted Spectral Color Correction. In 31st Color and Imaging Conference - Color Science and Engineering Systems, Technologies, and Applications, CIC 2023 (pp.33-37). Society for Imaging Science and Technology [10.2352/cic.2023.31.1.7].
File in questo prodotto:
File Dimensione Formato  
Buzzelli-2023-31 Color Imaging Conf-VoR.pdf

Solo gestori archivio

Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Licenza: Tutti i diritti riservati
Dimensione 292.57 kB
Formato Adobe PDF
292.57 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/469560
Citazioni
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
Social impact