Adaptive rule-based colour component weight assignment strategy for underwater video enhancement

ABSTRACTABSTRACTImages and videos collected in an underwater environment often have low contrast, blur, and colour cast due to two significant sources of distortion; light scattering and absorption. In an underwater image/video, suspended particles attenuate red and blue components more than green channels. This article presents two adaptive weight allocation strategies based on rule assignment for red, green, and blue channels. Firstly, an improved balanced contrast enhancement technique (IBCET) is proposed using an adaptive contrast enhancement scheme based on colour component weight assignment. Secondly, a modified fuzzy contrast enhancement technique which obtains the intensification factor based on the weight of each component is developed. Finally, principal component analysis fusion is employed to improve the overall colour and contrast of the output video frames. Qualitative and quantitative evaluations on the standard underwater video dataset are demonstrated to validate the improved performance of the proposed algorithm.KEYWORDS: Underwater video enhancement; underwater image enhancement; improved balanced contrast enhancement techniquemodified fuzzy intensification operatorcontrast enhancementimage and video contrast enhancementadaptive contrast enhancementPCA fusion Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsJitendra P. SonawaneJitendra P. Sonawane has received his B. E. and M. E. in Electronics and Telecommunication Engineering in 2012 & 2014 respectively from University of Mumbai. He is currently pursuing Ph. D. in area of image processing from the Electronics and Telecommunication Engineering department from the University of Mumbai. His research interest includes image processing, machine learning, embedded system, additive manufacturing.Mukesh D. PatilMukesh D. Patil is the Principal of Ramrao Adik Institute of Technology, Navi Mumbai, India. He obtained his Master of Technology and a PhD from the systems and control engineering, Indian Institute of Technology Bombay, Mumbai, India, in 2002 and 2013. His current research areas include robust control, fractional order control and signal processing. He is also involved with the implementation of numerical algorithms in fractional calculus with graphics processing unit (GPU) computing and hardware realization of linear and nonlinear fractional-order and complex-order systems. He has published over 40-refereed papers and several patents, most in the areas of fractional-order control and signal processing. He has served on the program committees of various conferences/workshops and member of several prestigious professional bodies.Gajanan K. BirajdarGajanan K. Birajdar obtained his M. Tech. (Electronics and Telecommunication Engineering) from Dr. Babasaheb Ambedkar Technological University, Maharashtra, India, in 2004 and Ph. D. in the area of blind image forensics from Nagpur University, India, in 2018. He is working in the Department of Electronics Engineering, Ramrao Adik Institute of Technology Nerul, Navi Mumbai, University of Mumbai. He is a member of various professional bodies like ISTE, IETE and IE(I). His current research interests are multimedia security and forensics.