Sparse And Redundant Image Representations Using Adaptive Dictionaries In Digital Image Denoising

Sparse and Redundant Image Representations Using Adaptive Dictionaries in Digital Image Denoising

Perceptual Digital Imaging

Visual perception is a complex process requiring interaction between the receptors in the eye that sense the stimulus and the neural system and the brain that are responsible for communicating and interpreting the sensed visual information. This process involves several physical, neural, and cognitive phenomena whose understanding is essential to design effective and computationally efficient imaging solutions. Building on advances in computer vision, image and video processing, neuroscience, and information engineering, perceptual digital imaging greatly enhances the capabilities of traditional imaging methods. Filling a gap in the literature, Perceptual Digital Imaging: Methods and Applications comprehensively covers the system design, implementation, and application aspects of this emerging specialized area. It gives readers a strong, fundamental understanding of theory and methods, providing a foundation on which solutions for many of the most interesting and challenging imaging problems can be built. The book features contributions by renowned experts who present the state of the art and recent trends in image acquisition, processing, storage, display, and visual quality evaluation. They detail advances in the field and explore human visual system-driven approaches across a broad spectrum of applications, including: Image quality and aesthetics assessment Digital camera imaging White balancing and color enhancement Thumbnail generation Image restoration Super-resolution imaging Digital halftoning and dithering Color feature extraction Semantic multimedia analysis and processing Video shot characterization Image and video encryption Display quality enhancement This is a valuable resource for readers who want to design and implement more effective solutions for cutting-edge digital imaging, computer vision, and multimedia applications. Suitable as a graduate-level textbook or stand-alone reference for researchers and practitioners, it provides a unique overview of an important and rapidly developing research field.

Denoising of Photographic Images and Video

This unique text/reference presents a detailed review of noise removal for photographs and video. An international selection of expert contributors provide their insights into the fundamental challenges that remain in the field of denoising, examining how to properly model noise in real scenarios, how to tailor denoising algorithms to these models, and how to evaluate the results in a way that is consistent with perceived image quality. The book offers comprehensive coverage from problem formulation to the evaluation of denoising methods, from historical perspectives to state-of-the-art algorithms, and from fast real-time techniques that can be implemented in-camera to powerful and computationally intensive methods for off-line processing. Topics and features: describes the basic methods for the analysis of signal-dependent and correlated noise, and the key concepts underlying sparsity-based image denoising algorithms; reviews the most successful variational approaches for image reconstruction, and introduces convolutional neural network-based denoising methods; provides an overview of the use of Gaussian priors for patch-based image denoising, and examines the potential of internal denoising; discusses selection and estimation strategies for patch-based video denoising, and explores how noise enters the imaging pipeline; surveys the properties of real camera noise, and outlines a fast approximation of nonlocal means filtering; proposes routes to improving denoising results via indirectly denoising a transform of the image, considering the right noise model and taking into account the perceived quality of the outputs. This concise and clearly written volume will be of great value to researchers and professionals working in image processing and computer vision. The book will also serve as an accessible reference for advanced undergraduate and graduate students in computer science, applied mathematics, and related fields. "The relentless quest for higher image resolution, greater ISO sensitivity, faster frame rates and smaller imaging sensors in digital imaging and videography has demanded unprecedented innovation and improvement in noise reduction technologies. This book provides a comprehensive treatment of all aspects of image noise including noise modelling, state of the art noise reduction technologies and visual perception and quantitative evaluation of noise.” Geoff Woolfe, Former President of The Society for Imaging Science and Technology. "This book on denoising of photographic images and video is the most comprehensive and up-to-date account of this deep and classic problem of image processing. The progress on its solution is being spectacular. This volume therefore is a must read for all engineers and researchers concerned with image and video quality." Jean-Michel Morel, Professor at Ecole Normale Supérieure de Cachan, France.