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Real-time enhancement using multi-linear adaptive gamma correction (MLAGC) for better night driving

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Abstract

In this paper, a real-time video-stream enhancement scheme is proposed along with a hardware prototype development. The proposed technique employs a multi-linear adaptive gamma correction method to locally enhance the dark video frames in presence of high intensity optical sources. The proposed algorithm employs three linear functions corresponding to low, medium and high intensity regions for proper enhancement of different intensity regions. The slope and range of the linear functions are automatically derived from intensity distribution and hence the overall multi-linear function becomes highly nonlinear and adaptive to varying constraints. Consequently, the input–output mapping function of the algorithm works as a spreading function in the low intensity range for contrast improvement and preserves the information of the high intensity regions to avoid information loss due to over-enhancement. The experimental results show that the proposed algorithm exhibits better performance than various existing algorithms in terms of subjective and objective measures.

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References

  1. Shi, Y., Yang, J., Wu, R., “Reducing Illumination Based on Nonlinear Gamma Correction,” 2007 IEEE International Conference on Image Processing, San Antonio, TX, pp. I - 529-I–532. 2007

  2. Shimoyama, S., Igarashi, M., Ikebe, M., Motohisa, J., “Local adaptive tone mapping with composite multiple gamma functions,” 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, pp. 3153–3156. 2009

  3. Gonzalez, R., Woods, R.: Digital image processing. In: Upper saddle river. Prentice Hall, Hoboken (2008)

    Google Scholar 

  4. Acharya, A., Giri, AV., “Contrast Improvement using Local Gamma Correction,” 6th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2020, pp. 110–114. 2020

  5. Shen, C-T., Lin, P-H., Lin, C-C., Yen, H-C., “Image enhancement using piecewise transfer functions with segmentations,” 2008 IEEE International Symposium on Consumer Electronics, Vilamoura, 2008. pp. 1-4

  6. Chiu, Y., Cheng, F., Huang, S., “Efficient contrast enhancement using adaptive gamma correction and cumulative intensity distribution,” IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, AK, 2011, pp. 2946–2950 (2011)

  7. Zhang, D., Park, W., Lee, S., Choi, K., Ko, S., “Histogram partition based gamma correction for image contrast enhancement,” IEEE 16th International Symposium on Consumer Electronics, Harrisburg, PA, 2012, pp. 1-4 (2012)

  8. Jung, C., Wang, X.: Detail-preserving tone mapping for low dynamic range displays with adaptive gamma correction. In: Dwara, M. (ed.) Visual communications and image processing (VCIP), pp. 1–5. IEEE, Singapore (2015)

    Google Scholar 

  9. Tiwari, M., Gupta, B., “Brightness preserving contrast enhancement of medical images using adaptive gamma correction and homomorphic filtering,” 2016 IEEE Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, pp. 1–4. 2016

  10. Li, Y., Liu, X., Liu, Y., “Adaptive Local Gamma Correction Based on Mean Value Adjustment,” 2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC), Qinhuangdao, pp. 1858–1863. 2015

  11. Singh, H., Kumar, A., Balyan, LK., Singh, GK., “Dark image enhancement using optimally compressed and equalized profile based parallel gamma correction,” 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, , pp. 1299–1303 (2017)

  12. Gautam, C., Tiwari, N., “Efficient color image contrast enhancement using Range Limited Bi-Histogram Equalization with Adaptive Gamma Correction,” 2015 International Conference on Industrial Instrumentation and Control (ICIC), Pune, pp. 175–180. 2015

  13. Huang, L., Cao, G., Yu, L., “Efficient contrast enhancement with truncated adaptive gamma correction,” 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Datong, pp. 189-194 (2016)

  14. Alizadeh, M., Talebpour, A., Soltanian-Zadeh, H., Aghamiri, SMR., “Effects of improved Adaptive Gamma Correction Method on Wireless Capsule Endoscopy images: Illumination compensation and edge detection,” 20th Iranian Conference on Electrical Engineering (ICEE2012), Tehran, pp. 1544–1548. (2012)

  15. Arriaga-Garcia, EF., Sanchez-Yanez, RE., Garcia-Hernandez, MG., “Image enhancement using Bi-Histogram Equalization with adaptive sigmoid functions,” 2014 International Conference on Electronics, Communications and Computers (CONIELECOMP), Cholula. pp. 28–34 (2014)

  16. Chang, Y., Jung, C., Ke, P., Song, H., Hwang, J.: Automatic contrast-limited adaptive histogram equalization with dual gamma correction. IEEE Access 6, 11782–11792 (2018)

    Article  Google Scholar 

  17. Huang, S., Cheng, F., Chiu, Y.: Efficient contrast enhancement using adaptive gamma correction with weighting distribution. IEEE Trans. Image Process. 22(3), 1032–1041 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  18. Chouhan, R., Jha, R.K., Biswas, P.K.: Enhancement of dark and low-contrast images using dynamic stochastic resonance. IET Image Proc. 7(2), 174–184 (2013)

    Article  MathSciNet  Google Scholar 

  19. Singh, H., Kumar, A., Balyan, L.K., Lee, H.: Fractional-order integration based fusion model for piecewise gamma correction along with textural improvement for satellite images. IEEE Access 7, 37192–37210 (2019)

    Article  Google Scholar 

  20. Agarwal, TK., Gupta, B., “An approach based on parametric sigmoid function for contrast enhancement with mean brightness preservation,” Proceedings of the 2014 IEEE Students' Technology Symposium, Kharagpur. pp. 247–252 (2014)

  21. Akter, N., Sultana, S., Faisal, RH., Rahman, MM., “BFAGC: A Bias-Free Adaptive Gamma Correction Method for Image Enhancement,” 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), Dhaka, Bangladesh. pp. 1–6 (2019)

  22. Kaur, R., Kaur, S., “Comparison of contrast enhancement techniques for medical image,” 2016 Conference on Emerging Devices and Smart Systems (ICEDSS), Namakkal. pp. 155–159 (2016)

  23. Abdani, SR., Zaki, WMDW., Hussain A., Mustapha, A., “An adaptive nonlinear enhancement method using sigmoid function for iris segmentation in pterygium cases,” 2015 International Electronics Symposium (IES), Surabaya. pp. 53-57 (2015)

  24. Srinivas, K., Bhandari, A.K.: Low light image enhancement with adaptive sigmoid transfer function. IET Image Process. 14(4), 668–678 (2020)

    Article  Google Scholar 

  25. Mahmood, A., Khan, S.A., Hussain, S., Almaghayreh, E.M.: An adaptive image contrast enhancement technique for low-contrast images. IEEE Access 7, 161584–161593 (2019)

    Article  Google Scholar 

  26. Sabine, E., Susstrunk, Winkler, S., “Color image quality on the Internet", Proc. SPIE 5304, Internet Imaging V, 15 December 2003

  27. Yu, W., Yao, H., Li, D., Li, G., Shi, H.: GLAGC: adaptive dual-gamma function for image illumination perception and correction in the wavelet domain. Sensors 21(3), 845 (2021)

    Article  Google Scholar 

  28. Loh, Y.P., Chan, C.S.: Getting to Know Low-light Images with the exclusively dark dataset. Comput Vis Image Understand 178, 30–42 (2019). https://doi.org/10.1016/j.cviu.2018.10.010

    Article  Google Scholar 

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Acknowledgements

The prototype development of this research work is sponsored by Silicon Institute of Technology Bhubaneswar, India.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Biju Patnaik University of Technology Odisha, Rourkela, India

    Abanikanta Pattanayak

  2. Department of Electronics and Communication Engineering, Silicon Institute of Technology, Bhubaneswar, India

    Aditya Acharya & Judhisthir Dash

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  1. Abanikanta Pattanayak
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  2. Aditya Acharya
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  3. Judhisthir Dash
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Abanikanta Pattanayak wrote the main manuscript. All authors reviewed the manuscript.

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Correspondence to Abanikanta Pattanayak.

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Pattanayak, A., Acharya, A. & Dash, J. Real-time enhancement using multi-linear adaptive gamma correction (MLAGC) for better night driving. J Real-Time Image Proc 20, 62 (2023). https://doi.org/10.1007/s11554-023-01320-9

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