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ABSTRACT
Haze and fog can significantly reduce the visibility of distant objects by scattering light and creating blurry, washed-out images lacking in detail. Image dehazing is a technique used in computer vision to enhance the clarity of such obscured images. This study examines the effectiveness of various dehazing methods using real hazy images and synthetic images with artificially created haze. Performance metrics such as PSNR, SSIM, MSE, CII, and computation time are used to evaluate the proposed method. The evaluation is carried out on datasets like RESIDE, GMAN, O-Haze, I-Haze, NH-Haze, and Dense haze to compare the proposed method with existing models. The proposed method attains 27.46%, 20.63% and 21.09% higher PSNR and 12.36%, 23.95% and 36.12% lower Natural Image Quality Evaluator for RESIDE dataset when analyzed to the existing models, such as strategic method towards contrast enhancement by 2D histogram equalization under TV decomposition (CE-TDHE-TVD), multiple level framework basis contrast enhancement for uniform with non-uniform back ground imageries utilizing appropriate histogram equalization (CE-VHE), and Contrast enhancement with brightness preservation of low light pictures with the help of combined CLAHE and BPDHE histogram equalization (CE-CLAHE-BPDHE) respectively.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
T. Surya Kavita
T. Surya Kavita received her B.Tech and M.Tech Degrees in Electronics and Communication Engineering from JNTU, Kakinada, India in 2000 and 2003 respectively, and presently pursuing Ph.D. in ECE department, JNTU, Kakinada, India. She has a total experience of 18 years in Teaching. She published more than 25 papers in various International and National journals. Her Research interests are Image Processing, Signal Processing, Compressive Sensing, Swarm Intelligence and Communications.
A. Vamsidhar
A. Vamsidhar received his B.Tech in Electronics and Communication Engineering from JNTU, Kakinada in 2000 and M.Tech in Digital Systems and Communications from National Institute of Technology, Calicut, Kerala in 2003. He received his Ph.D. in Electronics and Communication Engineering from Andhra University, Visakhapatnam, India in 2018. He has more than 20 years of teaching experience in various academic institutions. He published more than 35 papers in various International and National journals and filed 2 patents. He received Best Academician Award from IJIEMR-Elsevier SSRN Research Awards in 2022. He is Executive Committee Member of IETE Visakhapatnam Centre. His areas of research include Signal Processing, Image & Video Processing, Speech processing, Machine Learning and Wireless Communications.
G. Sunil Kumar
G. Sunil Kumar received his B.Tech and M.Tech degrees in Electronics and Communications Engineering from GIET, Gunupur, Odisha in 2008 and 2012 respectively, and presently pursuing Ph.D. in Electronics and Communication Engineering, University of Technology, Jaipur, India. He has more than 14 years of teaching experience in various academic institutions. He has authored or co-authored over 6 technical publications and filed 1 patent. His current research interests include Wireless Sensor Networks, Image processing and Swarm Intelligence.
G. V. Sridhar
G. V. Sridhar received his Ph.D., M.E and B.E in Electronics and Communications Engineering from Andhra University, Visakhapatnam, India in 2017, 2005 and 1998 respectively. He published 20 articles in various reputed national/international journals and conferences. He has more than 20 years of teaching experience in various academic institutions. His research interests include Bio-Medical Signal processing, Prosthetic Devices and Medical Electronics. He is a senior member of IEEE and a life member of IETE.
Y. Pavan Chaitanya
Y. Pavan Chaitanya completed his four year bachelor degree (B.Tech) in the stream of Electronics and Communication Engineering department from Raghu Engineering College, Visakhapatnam, India from 2018-2022. He worked on many case studies in different Signal Processing domains, and participated in many project presentations. His research interests are Image and Signal processing.
K. Mohan Babu
K. Mohan Babu received his Diploma degree in Electronics and Communication Engineering in 2019 and completed B.Tech in the stream of Electronics and Communication Engineering department from Raghu Engineering College, Visakhapatnam, India in 2022. He had done various projects and mostly interested in Image and Signal Processing.