Image denoising is a process to restore a noisy image so that the other system (or human) can understand it better. Since denoising is a challenging ill-posed problem, it has attracted many researchers. In this book, we discuss some efficient approaches for image denoising using wavelet transforms. For the last decade, wavelet-based approaches have been studied widely due to its superb performance and nice properties such as multiresolution and energy compaction.The book contains mainly following contents: First, some important wavelet transforms for image denoising are described. Second, a review on various denoising algorithms will help readers understand the trend. Some efficient algorithms take account into spatial and scale dependency in the wavelet domain or statistical modeling with Bayesian approach. The experimental results on various wavelet-based algorithms are also analyzed. Wavelet-based methods produce comparatively higher signal to noise ratio and less visual artifact than other methods.The book is addressed to students, graduates, professionals, and researchers who are interested in image processing.
Image denoising is a process to restore a noisy image so that the other system (or human) can understand it better. Since denoising is a challenging ill-posed problem, it has attracted many researchers. In this book, we discuss some efficient approaches for image denoising using wavelet transforms. For the last decade, wavelet-based approaches have been studied widely due to its superb performance and nice properties such as multiresolution and energy compaction.The book contains mainly following contents: First, some important wavelet transforms for image denoising are described. Second, a review on various denoising algorithms will help readers understand the trend. Some efficient algorithms take account into spatial and scale dependency in the wavelet domain or statistical modeling with Bayesian approach. The experimental results on various wavelet-based algorithms are also analyzed. Wavelet-based methods produce comparatively higher signal to noise ratio and less visual artifact than other methods.The book is addressed to students, graduates, professionals, and researchers who are interested in image processing.
Master's Thesis from the year 2016 in the subject Electrotechnology, grade: P5, Edinburgh Napier University, course: M.Sc in Electronics and Electricals - Digital signal processing, language:...
Presents a review of image denoising algorithms with practical MATLAB implementation guidance Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising,...
This dissertation describes research into image processing techniques that enhance military operational and support activities. The research extends existing work on image registration by introducing...
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