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Author: Omar Abdulrahman Alaql Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The last decade has witnessed great advances in digital images. Massive numbers of digital images are being captured by mobile digital cameras due to the increasing popularity of mobile imaging devices. These images are subjected to many processing stages during storing, transmitting, or sharing over a network connection. Unfortunately, these processing stages could potentially add visual degradation to original image. These degradations reduce the perceived visual quality which leads to an unsatisfactory experience for human viewers. Therefore, Image Quality Assessment (IQA) has become a topic of high interest and intense research over the last decade. The aim of IQA is to automatically assess image quality in agreement with human judgments.This dissertation mainly focuses on the most challenging category of IQA - general- purpose No-Reference Image Quality Assessment (NR-IQA), where the goal is to assess the quality of images without information about the reference images and without prior knowledge about the types of distortions in the tested image. This dissertation contributes to the research of image quality assessment by proposing three novel approaches for NR- IQA and one model for image distortions classification. First, we propose improvements in image distortions classification by introducing a training model based on new features collection. Second, we propose a NR-IQA technique, which utilizes our improvement in the classification model, and based on a hypothesis that an effective combination of image features can be used to develop efficient NR-IQA approaches. Third, a NR-IQA technique is proposed based on Natural Scene Statistics (NSS) by finding the distance between the natural images and the distorted images in 3D dimensional space. Forth, a novel NR-IQA approach is presented, by utilizing multiple Deep Belief Networks (DBNs) with multiple regression models. We have evaluated the performance of the proposed and some existing models on a fair basis. The obtained results show that our models give better results and yield a significant improvement.
Author: Omar Abdulrahman Alaql Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The last decade has witnessed great advances in digital images. Massive numbers of digital images are being captured by mobile digital cameras due to the increasing popularity of mobile imaging devices. These images are subjected to many processing stages during storing, transmitting, or sharing over a network connection. Unfortunately, these processing stages could potentially add visual degradation to original image. These degradations reduce the perceived visual quality which leads to an unsatisfactory experience for human viewers. Therefore, Image Quality Assessment (IQA) has become a topic of high interest and intense research over the last decade. The aim of IQA is to automatically assess image quality in agreement with human judgments.This dissertation mainly focuses on the most challenging category of IQA - general- purpose No-Reference Image Quality Assessment (NR-IQA), where the goal is to assess the quality of images without information about the reference images and without prior knowledge about the types of distortions in the tested image. This dissertation contributes to the research of image quality assessment by proposing three novel approaches for NR- IQA and one model for image distortions classification. First, we propose improvements in image distortions classification by introducing a training model based on new features collection. Second, we propose a NR-IQA technique, which utilizes our improvement in the classification model, and based on a hypothesis that an effective combination of image features can be used to develop efficient NR-IQA approaches. Third, a NR-IQA technique is proposed based on Natural Scene Statistics (NSS) by finding the distance between the natural images and the distorted images in 3D dimensional space. Forth, a novel NR-IQA approach is presented, by utilizing multiple Deep Belief Networks (DBNs) with multiple regression models. We have evaluated the performance of the proposed and some existing models on a fair basis. The obtained results show that our models give better results and yield a significant improvement.
Author: Alan C. Bovik Publisher: Academic Press ISBN: 0080533612 Category : Technology & Engineering Languages : en Pages : 1429
Book Description
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: Zhou Wang Publisher: Springer Nature ISBN: 3031022386 Category : Technology & Engineering Languages : en Pages : 146
Book Description
This Lecture book is about objective image quality assessment—where the aim is to provide computational models that can automatically predict perceptual image quality. The early years of the 21st century have witnessed a tremendous growth in the use of digital images as a means for representing and communicating information. A considerable percentage of this literature is devoted to methods for improving the appearance of images, or for maintaining the appearance of images that are processed. Nevertheless, the quality of digital images, processed or otherwise, is rarely perfect. Images are subject to distortions during acquisition, compression, transmission, processing, and reproduction. To maintain, control, and enhance the quality of images, it is important for image acquisition, management, communication, and processing systems to be able to identify and quantify image quality degradations. The goals of this book are as follows; a) to introduce the fundamentals of image quality assessment, and to explain the relevant engineering problems, b) to give a broad treatment of the current state-of-the-art in image quality assessment, by describing leading algorithms that address these engineering problems, and c) to provide new directions for future research, by introducing recent models and paradigms that significantly differ from those used in the past. The book is written to be accessible to university students curious about the state-of-the-art of image quality assessment, expert industrial R&D engineers seeking to implement image/video quality assessment systems for specific applications, and academic theorists interested in developing new algorithms for image quality assessment or using existing algorithms to design or optimize other image processing applications.
Author: Ashish Khare Publisher: Springer ISBN: 9811326851 Category : Technology & Engineering Languages : en Pages : 595
Book Description
This book presents select papers from the International Conference on Emerging Trends in Communication, Computing and Electronics (IC3E 2018). Covering the latest theories and methods in three related fields – electronics, communication and computing, it describes cutting-edge methods and applications in the areas of signal and image processing, cyber security, human-computer interaction, machine learning, electronic devices, nano-electronics, wireless sensor networks, antenna and wave propagation, and mobile communication. The contents of this book will be beneficial to students, researchers, and professionals working in the field of networks and communications.
Author: Zhouchen Lin Publisher: Springer Nature ISBN: 3030317234 Category : Computers Languages : en Pages : 813
Book Description
The three-volume set LNCS 11857, 11858, and 11859 constitutes the refereed proceedings of the Second Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019, held in Xi’an, China, in November 2019. The 165 revised full papers presented were carefully reviewed and selected from 412 submissions. The papers have been organized in the following topical sections: Part I: Object Detection, Tracking and Recognition, Part II: Image/Video Processing and Analysis, Part III: Data Analysis and Optimization.
Author: Yong Man Ro Publisher: Springer Nature ISBN: 3030377318 Category : Computers Languages : en Pages : 860
Book Description
The two-volume set LNCS 11961 and 11962 constitutes the thoroughly refereed proceedings of the 25th International Conference on MultiMedia Modeling, MMM 2020, held in Daejeon, South Korea, in January 2020. Of the 171 submitted full research papers, 40 papers were selected for oral presentation and 46 for poster presentation; 28 special session papers were selected for oral presentation and 8 for poster presentation; in addition, 9 demonstration papers and 6 papers for the Video Browser Showdown 2020 were accepted. The papers of LNCS 11961 are organized in the following topical sections: audio and signal processing; coding and HVS; color processing and art; detection and classification; face; image processing; learning and knowledge representation; video processing; poster papers; the papers of LNCS 11962 are organized in the following topical sections: poster papers; AI-powered 3D vision; multimedia analytics: perspectives, tools and applications; multimedia datasets for repeatable experimentation; multi-modal affective computing of large-scale multimedia data; multimedia and multimodal analytics in the medical domain and pervasive environments; intelligent multimedia security; demo papers; and VBS papers.
Author: Ming Jiang Publisher: Springer ISBN: 3319916599 Category : Technology & Engineering Languages : en Pages : 421
Book Description
This book collects a number of papers presented at the International Conference on Sensing and Imaging, which was held at Chengdu University of Information Technology on June 5-7, 2017. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, mathematics, and computing technology. The field has diverse applications of interest such as sensing techniques, imaging, and image processing techniques. This book will appeal to professionals and researchers within the field.
Author: Kohei Arai Publisher: Springer ISBN: 3030228681 Category : Technology & Engineering Languages : en Pages : 1295
Book Description
This book presents the proceedings of the Computing Conference 2019, providing a comprehensive collection of chapters focusing on core areas of computing and their real-world applications. Computing is an extremely broad discipline, encompassing a range of specialized fields, each focusing on particular areas of technology and types of application, and the conference offered pioneering researchers, scientists, industrial engineers, and students from around the globe a platform to share new ideas and development experiences. Providing state-of-the-art intelligent methods and techniques for solving real- world problems, the book inspires further research and technological advances in this important area.
Author: Marius Pedersen Publisher: Foundations and Trends(r) in C ISBN: 9781601985262 Category : Computers Languages : en Pages : 94
Book Description
This text surveys one full-reference image quality metrics. It starts by classifying these image quality metrics into four different groups and then selects further image quality metrics from each group and evaluates them against six state-of-the-art image quality databases.
Author: Lu Fang Publisher: Springer Nature ISBN: 3030930491 Category : Computers Languages : en Pages : 446
Book Description
This two-volume set LNCS 13069-13070 constitutes selected papers presented at the First CAAI International Conference on Artificial Intelligence, held in Hangzhou, China, in June 2021. Due to the COVID-19 pandemic the conference was partially held online. The 105 papers were thoroughly reviewed and selected from 307 qualified submissions. The papers are organized in topical sections on applications of AI; computer vision; data mining; explainability, understandability, and verifiability of AI; machine learning; natural language processing; robotics; and other AI related topics.
Author: Omar Abdulrahman Alaql
Author: Omar Abdulrahman Alaql
Author: Alan C. Bovik
Author: Zhou Wang
Author: Ashish Khare
Author: Zhouchen Lin
Author: Yong Man Ro
Author: Ming Jiang
Author: Kohei Arai
Author: Marius Pedersen
Author: Lu Fang