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Motion-Free Super-Resolution
With the explosion of Internet technology and graphics engines, digital images are now everywhere. Image capturing tools are all pervading - in our pockets to inside a satellite. And although imaging applications demand an availability to high resolution images, such images are not picture perfect and may be lacking sufficient details. This requires that these images be super-resolved for improved details. How to achieve this is what constitutes research in the area of image super-resolution. Motion-Free Super-Resolution explores new technology for image super-resolution - applying cues other than the motion cue in super-resolving a scene. This book will serve as an essential reference for both academecians and practicing engineers in the area of image processing and computer vision, as well as providing a basis for ongoing research in this field.
Image Processing : Dealing with Texture ; 2nd ed.
Updates the classic work on texture analysis theory and methods without abandoning the foundational essentials of this landmark work. Like the first, the new edition offers an analysis of texture in digital images that are essential to a diverse range of applications such as: robotics, defense, medicine and the geo-sciences. Designed to easily locate information on specific problems, the text is structured around a series of helpful questions and answers. Updated to include the most recent developments in the field, many chapters have been completely revised including: Fractals and Multifractals, Image Statistics, Texture Repair, Local Phase Features, Dual Tree Complex Wavelet Transform, Ridgelets and Curvelets and Deep Texture Features. The book takes a two-level mathematical approach: light math is covered in the main level of the book, with harder math identified in separate boxes.
Hexagonal image processing : A practical approach
Hexagonal Image Processing provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates. Digital image processing is currently dominated by the use of square sampling lattices, however, hexagonal sampling lattices can also be used to define digital images. The strengths offered by hexagonal lattices over square lattices are considerable: • higher packing density, • uniform connectivity of points (pixels) in the lattice, • better angular resolution by virtue of having more nearest neighbours, and • superlative representation of curves. The utility of the HIP framework is demonstrated by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. The HIP framework serves as a tool for comparing processing of images defined on a square vs hexagonal grid, to determine their relative merits and demerits. The theory and algorithms covered are supplemented by attention to practical details such as accommodating hardware that support only images sampled on a square lattice. Including a Foreword written by Professor Narendra Ahuja, an eminent researcher in the field of Image Processing and Computer Vision, the book’s fresh approach to the subject offers insight and workable know-how to both researchers and postgraduates.
From Gestalt Theory to Image Analysis : A Probabilistic Approach
This book introduces the reader to a recent theory in Computer Vision yielding elementary techniques to analyse digital images. These techniques are inspired from and are a mathematical formalization of the Gestalt theory. Gestalt theory, which had never been formalized is a rigorous realm of vision psychology developped between 1923 and 1975. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis.
Dental Digital Photography : From Dental Clinical Photography to Digital Smile Design
This book provides comprehensive and updated knowledge about dental digital photography. The first part focuses on the fundamental theory of photography, how to select photographic equipment and the basic applications of digital photography in various aspect in dentistry. The second part of the book summaries the different category of digital images.
Creating and Enhancing Digital Astro Images
Digital imaging is now available to all amateur astronomers at a reasonable price. The advent of CCDs, DSLRs and – perhaps most significantly – webcams mean today’s astronomers can make colorful planetary or deep-sky images of breathtaking beauty. The results obtained with even modest equipment can be spectacular, but of course they depend crucially on the computer processing of the images after they have been captured. Enhancing Digital Images is not just an introduction to image processing, it is a deeply practical, comprehensive and fully illustrated in-depth guide to using a digital camera, performing image reduction and undertaking image enhancement – all without jargon or math. Here is everything you need to know about processing digital astronomical images, regardless of whether you are experienced or a relative beginner!
Content based image retrieval systems
With an advent of technology, huge collection of digital images is formed as repositories on crime prevention, medical diagnosis, military, face finding, satellites and remote sensing. The task of searching for similar images in the repository is difficult. The data is growing enormously which makes it difficult to store and manage. The traditional image retrieval technique is inefficient in retrieving these images. Content-based image retrieval is an approach from data mining community, which provides the solution of managing this huge quantity of data. In this research, a Content-Based Image Retrieval (CBIR) system has been developed using color and texture as retrieval features from the image repository. The system allows the user to search for an image based on any of the two features alone or in combination by assigning weights to the features. The histogram and color moments approach is used to extract the color feature, texture feature is extracted using statistical moments and co-occurrence matrix method and the shape feature is extracted using the morphological operations. The images and the extracted feature vectors are stored in the Pickle file. The system is robust as it provides search based on the multiple features. The performance of the system was evaluated by analyzing the retrieval results using precision and recall.
Machine Learning for Multimedia Content Analysis
Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
Beginning Ubuntu Linux : From novice to professional
Beginning Ubuntu Linux is the perfect guide for those switching to the world's favorite Linux. The new edition has been thoroughly updated to cover technology introduced in the 6.10 release. You'll learn how to install Linux, set up your hardware and software, customize the desktop experience, browse the Web and send/receive e-mail, play back audio and video, edit digital images, use the OpenOffice.org office suite, and more.
Applied Graph Theory in Computer Vision and Pattern Recognition
It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks.
Adobe Photoshop CC Classroom in a Book
The 15 project-based lessons show key step-by-step techniques for working in Photoshop, including how to correct, enhance, and distort digital images, create image composites, and prepare images for print and the web. In addition to learning the essential elements of the Photoshop interface, this revised edition for the 2018 release covers features like search capabilities, Content-Aware Crop, Select and Mask, Face-Aware Liquify, designing with multiple artboards, creating and organising enhanced brush presets, and much more!
