HDR Image Watermarking

In this Chapter we survey available solutions for HDR image watermarking. First, we briefly discuss watermarking in general terms, with particular emphasis on its requirements that primarily include security, robustness, imperceptibility, capacity and the availability of the original image during recovery. However, with respect to traditional image watermarking, HDR images possess a unique set of features such as an extended range of luminance values to work with and tone-mapping operators against whom it is essential to be robust. These clearly affect the HDR watermarking algorithms proposed in the literature, which we extensively review next, including a thorough analysis of the reported experimental results. As a working example, we also describe the HDR watermarking system that we recently proposed and that focuses on combining imperceptibility, security and robustness to TM operators at the expense of capacity. We conclude the chapter with a critical analysis of the current state and future directions of the watermarking applications in the HDR domain

High-capacity watermarking of high dynamic range images

High dynamic range (HDR) imaging techniques address the need to capture the full range of color and light that the human eyes can perceive in the real world. HDR technology is becoming more and more pervasive. In fact, most of the cameras and smartphones available on the market are capable of capturing HDR images. Among the challenges posed by the spread of this new technology there is the increasing need to design proper techniques to protect the intellectual property of HDR digital media. In this paper, we speculate about the use of watermarking techniques to cope with the peculiarities of HDR media to prevent the misappropriation of HDR images

High Dynamic Range Image Watermarking Robust Against Tone-Mapping Operators

High dynamic range (HDR) images represent the future format for digital images since they allow accurate rendering of a wider range of luminance values. However, today special types of preprocessing, collectively known as tone-mapping (TM) operators, are needed to adapt HDR images to currently existing displays. Tone-mapped images, although of reduced dynamic range, have nonetheless high quality and hence retain some commercial value. In this paper, we propose a solution to the problem of HDR image watermarking, e.g., for copyright embedding, that should survive TM. Therefore, the requirements imposed on the watermark encompass imperceptibility, a certain degree of security, and robustness to TM operators. The proposed watermarking system belongs to the blind, detectable category; it is based on the quantization index modulation (QIM) paradigm and employs higher order statistics as a feature. Experimental analysis shows positive results and demonstrates the system effectiveness with current state-of-art TM algorithms

High Dynamic Range Visual Content Compression

This thesis addresses the research questions of High Dynamic Range (HDR) visual contents compression. The HDR representations are intended to represent the actual physical value of the light rather than exposed value. The current HDR compression schemes are the extension of legacy Low Dynamic Range (LDR) compressions, by using Tone-Mapping Operators (TMO) to reduce the dynamic range of the HDR contents. However, introducing TMO increases the overall computational complexity, and it causes the temporal artifacts. Furthermore, these compression schemes fail to compress non-salient region differently than the salient region, when Human Visual System (HVS) perceives them differently. The main contribution of this thesis is to propose a novel Mapping-free visual saliency-guided HDR content compression scheme. Firstly, the relationship of Discrete Wavelet Transform (DWT) lifting steps and TMO are explored. A novel approach to compress HDR image by Joint Photographic Experts Group (JPEG) 2000 codec while backward compatible to LDR is proposed. This approach exploits the reversibility of tone mapping and scalability of DWT. Secondly, the importance of the TMO in the HDR compression is evaluated in this thesis. A mapping-free post HDR image compression based on JPEG and JPEG2000 standard codecs for current HDR image formats is proposed. This approach exploits the structure of HDR formats. It has an equivalent compression performance and the lowest computational complexity compared to the existing HDR lossy compressions (50% lower than the state-of-the-art). Finally, the shortcomings of the current HDR visual saliency models, and HDR visual saliency-guided compression are explored in this thesis. A spatial saliency model for HDR visual content outperform others by 10% for spatial visual prediction task with 70% lower computational complexity is proposed. Furthermore, the experiment suggested more than 90% temporal saliency is predicted by the proposed spatial model. Moreover, the proposed saliency model can be used to guide the HDR compression by applying different quantization factor according to the intensity of predicted saliency map

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)

The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment. FMER is a subset of image processing and it is a multidisciplinary topic to analysis. So, it requires familiarity with other topics of Artifactual Intelligence (AI) such as machine learning, digital image processing, psychology and more. So, it is a great opportunity to write a book which covers all of these topics for beginner to professional readers in the field of AI and even without having background of AI. Our goal is to provide a standalone introduction in the field of MFER analysis in the form of theorical descriptions for readers with no background in image processing with reproducible Matlab practical examples. Also, we describe any basic definitions for FMER analysis and MATLAB library which is used in the text, that helps final reader to apply the experiments in the real-world applications. We believe that this book is suitable for students, researchers, and professionals alike, who need to develop practical skills, along with a basic understanding of the field. We expect that, after reading this book, the reader feels comfortable with different key stages such as color and depth image processing, color and depth image representation, classification, machine learning, facial micro-expressions recognition, feature extraction and dimensionality reduction. The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment.Comment: This is the second edition of the boo

Education handbook

2003 handbook for the faculty of Educatio