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Image Denoising Using Wavelet Transforms

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29 April 2008
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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.

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    Product Details
    ISBN-13
    9783836439183
    Author
    Dongwook Cho
    Publisher
    KS OmniScriptum Publishing
    Published
    29 April 2008
    Format
    Paperback / softback

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    RRP: $64.03
    $62.75
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Image Denoising Using Wavelet Transforms

    RRP: $64.03
    $62.75

    Description

    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.

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