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| Author | : Michael Joseph Horowitz |
| Publisher | : |
| Total Pages | : 292 |
| Release | : 1998 |
| Genre | : |
| ISBN | : |
| Author | : Alan C. Bovik |
| Publisher | : Academic Press |
| Total Pages | : 877 |
| Release | : 2009-07-08 |
| Genre | : Technology & Engineering |
| ISBN | : 0080922511 |
A complete introduction to the basic and intermediate concepts of image processing from the leading people in the field Up-to-date content, including statistical modeling of natural, anistropic diffusion, image quality and the latest developments in JPEG 2000 This comprehensive and state-of-the art approach to image processing gives engineers and students a thorough introduction, and includes full coverage of key applications: image watermarking, fingerprint recognition, face recognition and iris recognition and medical imaging. "This book combines basic image processing techniques with some of the most advanced procedures. Introductory chapters dedicated to general principles are presented alongside detailed application-orientated ones. As a result it is suitably adapted for different classes of readers, ranging from Master to PhD students and beyond." – Prof. Jean-Philippe Thiran, EPFL, Lausanne, Switzerland "Al Bovik’s compendium proceeds systematically from fundamentals to today’s research frontiers. Professor Bovik, himself a highly respected leader in the field, has invited an all-star team of contributors. Students, researchers, and practitioners of image processing alike should benefit from the Essential Guide." – Prof. Bernd Girod, Stanford University, USA "This book is informative, easy to read with plenty of examples, and allows great flexibility in tailoring a course on image processing or analysis." – Prof. Pamela Cosman, University of California, San Diego, USA A complete and modern introduction to the basic and intermediate concepts of image processing – edited and written by the leading people in the field An essential reference for all types of engineers working on image processing applications Up-to-date content, including statistical modelling of natural, anisotropic diffusion, image quality and the latest developments in JPEG 2000
| Author | : Alan C. Bovik |
| Publisher | : Academic Press |
| Total Pages | : 1429 |
| Release | : 2010-07-21 |
| Genre | : Technology & Engineering |
| ISBN | : 0080533612 |
55% new material in the latest edition of this “must-have for students and practitioners of image & video processing! This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today’s explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader’s own potential applications About the Editor... Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994. * No other resource for image and video processing contains the same breadth of up-to-date coverage * Each chapter written by one or several of the top experts working in that area * Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various, image-intensive disciplines
| Author | : Ee-Leng Tan |
| Publisher | : Springer |
| Total Pages | : 74 |
| Release | : 2015-05-13 |
| Genre | : Technology & Engineering |
| ISBN | : 9812875433 |
This book first introduces classic as well as recent computational models for just-noticeable-difference (JND) applications. Since the discrete cosine transform (DCT) is applied in many image and video standards (JPEG, MPEG-1/2/4, H.261/3), the book also includes a comprehensive survey of computational models for JND that are based on DCT. The visual factors used in these computational models are reviewed in detail. Further, an extensive comparative analysis of these models using quantitative and qualitative performance criteria is presented, which compares the noise shaping performance of these models with subjective evaluation and the accuracy between the estimated JND thresholds and subjective evaluation. There are many surveys available on computational models for JND; however, these surveys seldom compare the performance of computational models that are based on DCT. The authors’ survey of the computational models and their in-depth review of the visual factors used in them will help readers understand perceptual image coding based on DCT. The book also provides a comparative analysis of several perceptual image coders that are based on DCT, which are compatible with the highly popular and widely adopted JPEG standard.
| Author | : Elham Etemad |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
The most essential technique in creating agents with the ability to process and understand the content of visual data is object recognition, which includes image content classi cation, and object localization. Deep convolutional neural networks' (CNNs) performance gain in computer vision, there still are application scenarios with limited training data and computing power for which using deep CNN based methods is not feasible. On the other hand, the human engineered image representations require less training data and computing power and can be enhanced by importing domain specif c knowledge. These representations may also bene fit from the human vision characteristics in reducing the gap between computed image representations and human vision perception. In this thesis we have proposed four methods to improve image classi cation and object localization. All these methods utilize the perceptual shape features of image since it is proved that the human vision perception on objects mostly relies on shape features of the objects, while color and texture are utilized as extra sources to complete this perception. In the rst method, we have created a static dictionary of perceptual shape features based on N-gram model and used that in combination with spatial pyramid matching to represent images. In the second method, a dynamic dictionary from image edge segments is formed where these segments are obtained from an octave of image in di erent scales. The third method considers the curve partitioning points as descriptive features of the image and created a dynamic dictionary from descriptors of these points. The proposed object localization method utilizes the perceptual shape features of the image to improve the location of objects determined by object recognition module. The initial location may be obtained by any object recognition method, then the proposed method iteratively merges the edge segments with the detected object using a best rst search strategy. These proposed methods have been evaluated on di erent benchmark image datasets. Judging on the overall performance of the proposed method, it is expected that the proposed methods would bring some useful alternatives to support e cient tool development for applications lacking training data or no training data at all.
| Author | : |
| Publisher | : |
| Total Pages | : 806 |
| Release | : 1997 |
| Genre | : Dissertation abstracts |
| ISBN | : |
| Author | : Yi Zhang |
| Publisher | : |
| Total Pages | : |
| Release | : 2016 |
| Genre | : Computers |
| ISBN | : |
Perceptual coding is a subdiscipline of image and video coding that uses models of human visual perception to achieve improved compression efficiency. Nearly, all image and video coders have included some perceptual coding strategies, most notably visual masking. Today, modern coders capitalize on various basic forms of masking such as the fact that distortion is harder to see in very dark and very bright regions, in regions with higher frequency content, and in temporal regions with abrupt changes. However, beyond these obvious forms of masking, there are many other masking phenomena that occur (and co-occur) when viewing natural imagery. In this chapter, we present our latest research in perceptual image coding using natural-scene masking models. We specifically discuss: (1) how to predict local distortion visibility using improved natural-scene masking models and (2) how to apply the models to high efficiency video coding (HEVC). As we will demonstrate, these techniques can offer 10-20% fewer bits than baseline HEVC in the ultra-high-quality regime.
| Author | : Damian Marcellinus Tan |
| Publisher | : |
| Total Pages | : 326 |
| Release | : 2003 |
| Genre | : Coding theory |
| ISBN | : |
| Author | : Susana Martinez-Conde |
| Publisher | : Elsevier |
| Total Pages | : 341 |
| Release | : 2006-10-05 |
| Genre | : Psychology |
| ISBN | : 0080466087 |
This book presents a collection of articles reflecting state-of-the-art research in visual perception, specifically concentrating on neural correlates of perception. Each section addresses one of the main topics in vision research today. Volume 1 Fundamentals of Vision: Low and Mid-Level Processes in Perception covers topics from receptive field analyses to shape perception and eye movements. A variety of methodological approaches are represented, including single-neuron recordings, fMRI and optical imaging, psychophysics, eye movement characterization and computational modelling. The contributions will provide the reader with a valuable perspective on the current status of vision research, and more importantly, with critical insight into future research directions and the discoveries yet to come. · Provides a detailed breakdown of the neural and psychophysical bases of Perception · Presents never-before-published original discoveries · Includes multiple full-color illustrations
| Author | : Raphael Jona Rom |
| Publisher | : |
| Total Pages | : 79 |
| Release | : 1975 |
| Genre | : Imaging systems |
| ISBN | : |
In recent years more and more attention was paid to digital image processing especially as a result of the development of highly efficient algorithms and also because of technologically better facilities. Concurrently attempts were made to find a mathematical model for human vision to achieve better understanding about that mechanism. Some of the image processing problems that were (and are) tackled are image enhancement, bandwidth reduction, image transmission, etc. Unfortunately very few have taken the mechanism of the human vision into consideration in their processes. This work is an attempt to incorporate the model of human vision in image transmission and coding. An optimal system is developed to transmit a digital image over a noisy channel. The same system is used for image bandwidth reduction utilizing a simple coding scheme which is not based on the knowledge of the statistics of the image in question. The improvement of the optimal system over other similar systems are demonstrated and provide explanation for situations where other systems failed. The model used for transmitting images can be also interpreted as the model of the visual mechanism itself and thus shed some light on human vision from a new interesting aspect.
