publication . Other literature type . Preprint . Conference object . 2018

Revisiting Gray Pixel for Statistical Illumination Estimation

Yanlin Qian; Said Pertuz; Jarno Nikkanen; Joni-Kristian Kämäräinen; Jiri Matas;
  • Published: 22 Mar 2018
  • Publisher: Scitepress
Abstract
We present a statistical color constancy method that relies on novel gray pixel detection and mean shift clustering. The method, called Mean Shifted Grey Pixel -- MSGP, is based on the observation: true-gray pixels are aligned towards one single direction. Our solution is compact, easy to compute and requires no training. Experiments on two real-world benchmarks show that the proposed approach outperforms state-of-the-art methods in the camera-agnostic scenario. In the setting where the camera is known, MSGP outperforms all statistical methods.
Subjects
arXiv: Computer Science::Computer Vision and Pattern RecognitionComputer Science::Multimedia
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: Computer Science - Computer Vision and Pattern Recognition, Computer vision, Gray (unit), Computer science, Artificial intelligence, business.industry, business, Pixel
Related Organizations
41 references, page 1 of 3

1. Foster, D.H.: Color constancy. Vision research 51(7) (2011) 674-700

2. Brainard, D.H., Wandell, B.A.: Analysis of the retinex theory of color vision. JOSA A 3(10) (1986) 1651-1661 [OpenAIRE]

3. Barnard, K., Cardei, V., Funt, B.: A comparison of computational color constancy algorithms. i: Methodology and experiments with synthesized data. TIP 11(9) (2002) 972-984 [OpenAIRE]

4. Van De Weijer, J., Gevers, T., Gijsenij, A.: Edge-based color constancy. TIP 16(9) (2007) 2207-2214

5. Finlayson, G.D., Trezzi, E.: Shades of gray and colour constancy. In: Color Imaging Conference (CIC). (2004)

6. Gao, S., Han, W., Yang, K., Li, C., Li, Y.: Fefficient color constancy with local surface reflectance statistics. In: ECCV. (2014)

7. Yang, K.F., Gao, S.B., Li, Y.J.: Efficient illuminant estimation for color constancy using grey pixels. In: CVPR. (2015)

8. Cheng, D., Prasad, D.K., Brown, M.S.: Illuminant estimation for color constancy: why spatial-domain methods work and the role of the color distribution. JOSA A 31(5) (May 2014) 1049-1058

9. Chakrabarti, A., Hirakawa, K., Zickler, T.: Color constancy with spatio-spectral statistics. TPAMI 34(8) (2012) 1509-1519

10. Gijsenij, A., Gevers, T., Van De Weijer, J.: Generalized gamut mapping using image derivative structures for color constancy. IJCV 86(2-3) (2010) 127-139

11. Gehler, P.V., Rother, C., Blake, A., Minka, T., Sharp, T.: Bayesian color constancy revisited. In: CVPR. (2008) [OpenAIRE]

12. Gijsenij, A., Gevers, T.: Color constancy using natural image statistics and scene semantics. TPAMI 33(4) (2011) 687-698 [OpenAIRE]

13. Joze, H.R.V., Drew, M.S.: Exemplar-based color constancy and multiple illumination. TPAMI 36(5) (2014) 860-873

14. Gao, S.B., Zhang, M., Li, C.Y., Li, Y.J.: Improving color constancy by discounting the variation of camera spectral sensitivity. JOSA A 34(8) (2017) 1448-1462

15. Shafer, S.A.: Using color to separate reflection components. Color Research & Application 10(4) (1985) 210-218 [OpenAIRE]

41 references, page 1 of 3
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Other literature type . Preprint . Conference object . 2018

Revisiting Gray Pixel for Statistical Illumination Estimation

Yanlin Qian; Said Pertuz; Jarno Nikkanen; Joni-Kristian Kämäräinen; Jiri Matas;