Abstract
Low-illumination image enhancement problem is a very challenging problem in many computer vision applications and, when it comes to nighttime low-illumination images, it becomes more challenging because the depth information of the low-illumination image is not known. Recently, bright channel prior-based methods are used to enhance the overall illumination of the image. The bright channel prior is based on statistical observation on the low-illumination image containing some regions with bright intensity pixels. In this paper, we propose an improved \(l_{2}\) norm-based prior bright channel to enhance the overall illumination of the image by maintaining the image contrast. This new generated bright channel is free from the block effect, which makes our method more robust than other methods. The experimental results show the effectiveness of the proposed method on the low-illumination images as well as on the nighttime low-illumination images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Vishalakshi GR, Gopalakrishna MT, Hanumantharaju MC (2016) In Comprehensive review of video enhancement algorithms for low lighting conditions. In: Satapathy S, Mandal J, Udgata S, Bhateja V (eds), Advances in intelligent systems and computing. Springer, New York, pp. 475–485
Wang ZY, Hang MW, Hu P (2006) Image enhancement based on histograms and its realization with MATLAB. Comput Eng Sci 28(2):54–56
Jiang DQ, Li MD, Mao JL (2013) The research of the luminance dark color image enhancement technology. Artif Intell Identif 20:81–82
Jinag JL, Zhang YS, Xue F (2006) Local histogram equalization with brightness preservation. ACTA ELECTRONICA SINICA 34(5):861–866
Pizer SM, Amburn EP, Austin JD, Cromartie R, Geselowitz A, Greer T, Romeny BH, Zimmerman JB, Zuiderveld K (1987) Adaptive histogram equalization and its variations, Comput Vis Graph Image Process 39 355–228 368
Zuiderveld K (1994) Contrast limited adaptive histogram equalization. In: Graphics Gems IV; Academic Press Professional Inc: 230 Cambridge. MA, USA, pp 474–485
Zhao F, Luo HY, Geng H (2014) An RSSI gradient-based AP localization algorithm. China Commun 11:100–108
Piao Y, Liu L, Liu XY (2014) Enhancement technology of video under low illumination. Infrared Laser Eng 43(6):2021–2026
Wang WB, Mu XY, Tang N (2014) Algorithm of low illumination image enhancement, computer and modernization, pp. 27–31
Tiwari M, Gupta B, Shrivastava M (2015) High-speed quantile-based histogram equalisation for brightness preservation and contrast enhancement. IET Image Process 9:80–89
Sun S, Guo X, Image enhancement using bright channel prior. In: 2016 International conference on industrial informatics–computing technology, intelligent technology, Industrial Information Integration. Wuhan, China, pp 83–86 (2016)
Singh D, Kumar V (2018) Single image haze removal using integrated dark and bright channel prior. Modern Phys Lett B 32:1–9
Shi Z, Zhu MM, Guo B, Zhao M, Zhang C (2018) Nighttime low illumination image enhancement with single image using bright/dark channel prior. EURASIP J Image Video Process 13:1–15
He K, Sun J, Tang X (2011) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341–2353
Loh YP, Chan CS (2019) Getting to know low-light images with the exclusively dark dataset. Comput Vision Image Understand 178
Wang Z, Bovik AC (2002) A universal image quality index. IEEE Signal Process Lett 9:81–84
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Riya, Gupta, B., Lamba, S.S. (2021). \(l_{2}\) Norm Prior-Based Modified Bright Channel for Low-Illumination Images. In: Giri, D., Buyya, R., Ponnusamy, S., De, D., Adamatzky, A., Abawajy, J.H. (eds) Proceedings of the Sixth International Conference on Mathematics and Computing. Advances in Intelligent Systems and Computing, vol 1262. Springer, Singapore. https://doi.org/10.1007/978-981-15-8061-1_40
Download citation
DOI: https://doi.org/10.1007/978-981-15-8061-1_40
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-8060-4
Online ISBN: 978-981-15-8061-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)