Current Optics and Photonics

Optical Society of Korea (한국광학회)
권호 표지
DOI QR코드

DOI QR Code

Colour Linear Array Image Enhancement Method with Constant Colour

  • Ji, Jing (State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University) ;
  • Fang, Suping (State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University) ;
  • Cheng, Zhiqiang (State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University)
  • Received : 2021.11.23
  • Accepted : 2022.03.07
  • Published : 2022.06.25
Download PDF
⟨ Previous Next ⟩

Abstract

Digital images of cultural relics captured using line scan cameras present limitations due to uneven intensity and low contrast. To address this issue, this report proposes a colour linear array image enhancement method that can maintain a constant colour. First, the colour linear array image is converted from the red-green-blue (RGB) colour space into the hue-saturation-intensity colour space, and the three components of hue, saturation, and intensity are separated. Subsequently, the hue and saturation components are held constant while the intensity component is processed using the established intensity compensation model to eliminate the uneven intensity of the image. On this basis, the contrast of the intensity component is enhanced using an improved local contrast enhancement method. Finally, the processed image is converted into the RGB colour space. The experimental results indicate that the proposed method can significantly improve the visual effect of colour linear array images. Moreover, the objective quality evaluation parameters are improved compared to those determined using existing methods.

Keywords

Acknowledgement

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

  1. P. Zhang, T. J. Arre, and A. Ide-Ektessabi, "A line scan camera-based structure from motion for high-resolution 3D reconstruction," J. Cult. Herit. 16, 656-663 (2015). https://doi.org/10.1016/j.culher.2015.01.003
  2. J. A. Toque, M. Komori, Y. Murayama, and A. Ide-Ektessabi, "Analytical imaging of traditional japanese paintings using mulitispectral images," in Proc. Computer Vision, Imaging and Computer Graphics. Theory and Applications (Lisboa, Portugal, Feb. 5-8, 2009), pp. 119-132.
  3. R. Kanai, Y. Kowada, P. Wang, P. M. Toiya, J. A. Toque, and A. Ide-Ektessabi, "A novel scanning technique for imaging of gold and silver foils used in art works," in Proc. Computational Color Imaging-CCIW (Milan, Italy, Mar. 29-31, 2017), pp. 150-162.
  4. X. Xia, S. Fang, and Y. Xiao, "High resolution image fusion algorithm based on multi-focused region extraction," Pattern Recognit. Lett. 45, 115-120 (2014). https://doi.org/10.1016/j.patrec.2014.03.018
  5. S. F. Tan and N. A. M. Isa, "Exposure based multi-histogram equalization contrast enhancement for non-uniform illumination images," IEEE Access 7, 70842-70861 (2019). https://doi.org/10.1109/access.2019.2918557
  6. T. L. Kong and N. A. M. Isa, "Bi-histogram modification method for non-uniform illumination and low-contrast images," Multimed. Tool. Appl. 77, 8955-8978 (2018). https://doi.org/10.1007/s11042-017-4789-4
  7. D. Wang, W. Yan, T. Zhu, Y. Xie, H. Song, and X. Hu, "An adaptive correction algorithm for non-uniform illumination panoramic images based on the improved bilateral gamma function," in Proc. International Conference on Digital Image Computing: Techniques and Applications-DICTA (Sydney, Australia, Nov. 29-Dec. 1, 2017), pp. 1-6.
  8. Z. Wang, H. Zhang, J. Liao, H. Guo, and Z. Zhang, "An adaptive gamma method for image under non-uniform illumination," Proc. SPIE 10256, 102561C (2017).
  9. M. F. A. Hassan, A. S. A. Ghani, D. Ramachandram, A. Radman, and S. A. Suandi, "Enhancement of under-exposed image for object tracking algorithm through homomorphic filtering and mean histogram matching," Adv. Sci. Lett. 23, 11257-11261 (2017). https://doi.org/10.1166/asl.2017.10262
  10. C.-C. Tseng and S.-L. Lee, "A weak-illumination image enhancement method using homomorphic filter and image fusion," in Proc. IEEE 6th Global Conference on Consumer Electronics-GCCE (Nagoya, Japan, Oct. 24-27, 2017), pp. 1-2.
  11. Z. Rao, T. Xu, and H. Wang, "Mission-critical monitoring based on surround suppression variational Retinex enhancement for non-uniform illumination images," EURASIP J. Wirel. Commun. Netw. 2017, 88 (2017). https://doi.org/10.1186/s13638-017-0872-9
  12. R. K. Xue and Y. F. Li, "Color image enhancement based on HVS and MSRCR," Proc. SPIE 9675, 967516 (2015).
  13. A. A. S. Gunawan and H. Setiadi, "Handling illumination variation in face recognition using multiscale Retinex," in Proc. International Conference on Advanced Computer Science and Information Systems-ICACSIS (Malang, Indonesia, Oct. 15-16, 2016), pp. 470-475.
  14. S. Fang, X. Xia, and Y. Xiao, "A calibration method of lens distortion for line scan cameras," Optik 124, 6749-6751 (2013). https://doi.org/10.1016/j.ijleo.2013.05.084
  15. S. Ma, H. Ma, Y. Xu, S. Li, C. Lv, and M. Zhu, "A low-light sensor image enhancement algorithm based on HSI color model," Sensors 18, 3583. (2018). https://doi.org/10.3390/s18103583
  16. X. Zhong, Y. Zhang, G. Jin, "Illumination uniformity optimization of wide-viewing-field optical system," Acta Opt. Sin. 32, 0322004 (2012). https://doi.org/10.3788/AOS201232.0322004
  17. L. Qin, L. Dong, and W. Xu, "Method for conversion calibration between CCD image gray value and illumination," Chin. J. Sci. Instrum. 36, 639-644 (2015).
  18. H. Yun, Y. Dong, and X. Wang, "Color image enhancement combining human visual characteristics with fuzzy set theory," J. Nanjing Normal Univ. (Eng. Tech.). 3, 25-32 (2018)..
  19. S. Wang, D. Gao, Y. Wang, and S. Wang, "An improved Retinex low-illumination image enhancement algorithm," in Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference-APSIPA ASC (Lanzhou, China, Nov. 18-21, 2019), pp. 1134-1139.
  20. S. Shao, Y. F. Guo, H. Liu, H. F. Yuan, and Z. S. Zhang, "Low-illumination remote sensing image enhancement in HSI color space," Opt. Precis. Eng. 26, 2092-2099 (2018). https://doi.org/10.3788/ope.20182608.2092
  21. L. Zhang, L. Yang, T. Luo, and Y. Sun, "A novel illumination compensation method with enhanced Retinex," in Proc. 3rd International Conference on Information Science and Control Engineering -ICISCE (Beijing, China, Jul. 8-10, 2016), pp. 83-87.
  22. H.R. Kang, Color technology for electronic imaging devices, (SPIE Press, USA, 1997).
  23. J. Ji, S. Fang, Z. Shi, Q. Xia, and Y. Li, "An efficient nonlinear polynomial color characterization method based on interrelations of color spaces," Color Res. Appl. 45,1023-1039 (2020). https://doi.org/10.1002/col.22563
  24. J. Ji, S. Fang, Q. Xia, and Z. Shic, "An efficient method for scanned images by using color-correction and L0 gradient minimization," Optik 247, 167820 (2021). https://doi.org/10.1016/j.ijleo.2021.167820
  25. A. Abrardo, V. Cappellini, M. Cappellini, and A. Mecocci. "Art-works colour calibration using the VASARI scanner," in Proc. 4th Color Imaging Conference (Scottsdale, USA, Nov. 19-22, 1996), p. 94C97.
  26. H. R. Sheikh, Z. Wang, L. Cormack, and A. C. Bovik, "LIVE image quality assessment database," (Laboratory for Image & Video Engineering of the University of Texas at Austin, Published: 2005), http://live.ece.utexas.edu/research/quality (Accessed: Sep. 10 , 2021).