ABSTRACT
Image recoloring using wavelet transform, in-painting and dichromatic reflection model is proposed. Detailed wavelet bands are passed through a sharpening filter whereas the approximation band is passed through dichromatic reflection model to extract body and specular coefficients. In-painting and white illumination minimization using erosion and Gaussian blur further enhance the image quality. The proposed technique produces better results, both qualitatively and quantitatively, in terms of edge preservation and minimization of noise, artefacts in contrast to state-of-art existing techniques.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes on contributors
Mehwish Iqbal is a Ph.D. student of electrical engineering from National University of Sciences and Technology (NUST), Pakistan. Her research interests include image processing, machine learning, computer vision and neural networks.
M. Mohsin Riaz obtained his Ph.D. degree in electrical engineering from National University of Sciences and Technology (NUST), Pakistan, in 2013. Currently he is Assistant Professor at COMSATS Institute of Information Technology, Pakistan. His research interests include image processing and machine learning.
Abdul Ghafoor received the B.S. degree in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan, in 1994, M.S. degree in electrical engineering from the National University of Sciences and Technology (NUST), Islamabad, Pakistan, in 2003, and the Ph.D. degree from the University of Western Australia (UWA) in 2007. His research topics include model/controller order reduction, image processing/matching, through wall imaging, and cognitive radio. Since 2008, he is with NUST, where he is currently an associate professor.
Attiq Ahmad obtained his Ph.D. degree in electrical engineering from National University of Sciences and Technology (NUST), Pakistan, in 2016. Currently he is Assistant Professor at NUST. His research interests include Image/Signal processing.