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This research work investigates visibility degradation due to poor weather conditions and pro- poses methods to improve the colour, contrast, and visibility of digital images taken under such conditions. It is common knowledge that digital images need post processing not only for better human perception but also to be fed as input to computer vision application systems. Visibility improvement is a process of restoring the true appearance, i.e. recovering what the scene should have looked like on a clear day, by enhancing the colour, contrast and sharpening the details. Amongst the ample…mehr

Produktbeschreibung
This research work investigates visibility degradation due to poor weather conditions and pro- poses methods to improve the colour, contrast, and visibility of digital images taken under such conditions. It is common knowledge that digital images need post processing not only for better human perception but also to be fed as input to computer vision application systems. Visibility improvement is a process of restoring the true appearance, i.e. recovering what the scene should have looked like on a clear day, by enhancing the colour, contrast and sharpening the details. Amongst the ample variety of algorithms proposed over the years in this direction, single image visibility improvement algorithms have emerged as the preferred ones for visibility improvement algorithms, due to their relative simplicity and accuracy. However, to deal with the de- mand in real time applications and increasing image resolution, there is an ever-growing need to develop newer schemes appropriate for single image visibility improvement with higher efficiency and lower computational complexity.
Autorenporträt
Sangita Roy è professore associato presso il Dipartimento ECE del Narula Institute of Technology, India. Ha un'esperienza di insegnamento di oltre ventisei anni. È stata per due anni alla Bells Controls Limited (industria della strumentazione) e per due anni al West Bengal State Centre, IEI (Kolkata) come coordinatore tecnico.