Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Digital watermarking methods for data security and authentication

Philosophiae Doctor - PhDCryptology is the study of systems that typically originate from a consideration of the ideal circumstances under which secure information exchange is to take place. It involves the study of cryptographic and other processes that might be introduced for breaking the output of such systems - cryptanalysis. This includes the introduction of formal mathematical methods for the design of a cryptosystem and for estimating its theoretical level of securit

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

Directional edge and texture representations for image processing

An efficient representation for natural images is of fundamental importance in image processing and analysis. The commonly used separable transforms such as wavelets axe not best suited for images due to their inability to exploit directional regularities such as edges and oriented textural patterns; while most of the recently proposed directional schemes cannot represent these two types of features in a unified transform. This thesis focuses on the development of directional representations for images which can capture both edges and textures in a multiresolution manner. The thesis first considers the problem of extracting linear features with the multiresolution Fourier transform (MFT). Based on a previous MFT-based linear feature model, the work extends the extraction method into the situation when the image is corrupted by noise. The problem is tackled by the combination of a "Signal+Noise" frequency model, a refinement stage and a robust classification scheme. As a result, the MFT is able to perform linear feature analysis on noisy images on which previous methods failed. A new set of transforms called the multiscale polar cosine transforms (MPCT) are also proposed in order to represent textures. The MPCT can be regarded as real-valued MFT with similar basis functions of oriented sinusoids. It is shown that the transform can represent textural patches more efficiently than the conventional Fourier basis. With a directional best cosine basis, the MPCT packet (MPCPT) is shown to be an efficient representation for edges and textures, despite its high computational burden. The problem of representing edges and textures in a fixed transform with less complexity is then considered. This is achieved by applying a Gaussian frequency filter, which matches the disperson of the magnitude spectrum, on the local MFT coefficients. This is particularly effective in denoising natural images, due to its ability to preserve both types of feature. Further improvements can be made by employing the information given by the linear feature extraction process in the filter's configuration. The denoising results compare favourably against other state-of-the-art directional representations

FPGA Prototyping of a Watermarking Algorithm for MPEG-4

In the immediate future, multimedia product distribution through the Internet will become main stream. However, it can also have the side effect of unauthorized duplication and distribution of multimedia products. That effect could be a critical challenge to the legal ownership of copyright and intellectual property. Many schemes have been proposed to address these issues; one is digital watermarking which is appropriate for image and video copyright protection. Videos distributed via the Internet must be processed by compression for low bit rate, due to bandwidth limitations. The most widely adapted video compression standard is MPEG-4. Discrete cosine transform (DCT) domain watermarking is a secure algorithm which could survive video compression procedures and, most importantly, attacks attempting to remove the watermark, with a visibly degraded video quality result after the watermark attacks. For a commercial broadcasting video system, real-time response is always required. For this reason, an FPGA hardware implementation is studied in this work. This thesis deals with video compression, watermarking algorithms and their hardware implementation with FPGAs. A prototyping VLSI architecture will implement video compression and watermarking algorithms with the FPGA. The prototype is evaluated with video and watermarking quality metrics. Finally, it is seen that the video qualities of the watermarking at the uncompressed vs. the compressed domain are only 1dB of PSNR lower. However, the cost of compressed domain watermarking is the complexity of drift compensation for canceling the drifting effect

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

A new approach for improving transparency of audio watermarking.

Chen Benrong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 125-130).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- What' s Watermarking --- p.1Chapter 1.2 --- "Information Hiding, Steganography, and Watermarking" --- p.3Chapter 1.3 --- History of Watermarking --- p.5Chapter 1.4 --- Importance of Digital Watermarking --- p.8Chapter 1.5 --- Objectives of the Thesis --- p.9Chapter 1.6 --- Thesis Outline --- p.10Chapter 2 --- Applications and Properties of Audio Watermarking --- p.12Chapter 2.1 --- Applications --- p.13Chapter 2.1.1 --- Ownership Identification and Proof --- p.13Chapter 2.1.2 --- Broadcast Monitoring --- p.16Chapter 2.1.3 --- Other Applications --- p.18Chapter 2.2 --- Properties --- p.19Chapter 2.2.1 --- Transparency --- p.20Chapter 2.2.2 --- Robustness --- p.20Chapter 2.2.3 --- Other Properties --- p.21Chapter 3 --- Possible Methods for Audio Watermarking --- p.24Chapter 3.1 --- Overview of Digital Audio Watermarking System --- p.25Chapter 3.2 --- Review of Current Methods --- p.27Chapter 3.2.1 --- Low Bit Coding --- p.27Chapter 3.2.2 --- Phase Coding --- p.28Chapter 3.2.3 --- Echo Coding --- p.29Chapter 3.2.4 --- Spread Spectrum Watermarking --- p.30Chapter 3.3 --- Other Related Approaches --- p.31Chapter 3.4 --- Outline of Proposed New Method --- p.33Chapter 4 --- Audio Watermarking System Based on Spread Spectrum --- p.36Chapter 4.1 --- Introduction --- p.36Chapter 4.2 --- Embedding and Detecting Information Bit --- p.39Chapter 4.2.1 --- General Embedding Process --- p.39Chapter 4.2.2 --- General Detection Process --- p.43Chapter 4.2.3 --- Pseudorandom Bit Sequences (PRBS) --- p.45Chapter 4.3 --- An Optimal Embedding Process --- p.48Chapter 4.3.1 --- Objective Metrics for Embedding Process --- p.48Chapter 4.3.2 --- Content Adaptive Embedding --- p.52Chapter 4.3.3 --- Determination of Frame Length L --- p.57Chapter 4.4 --- Requirement For Transparency Improvement --- p.58Chapter 5 --- Sample and Frame Selection For Transparency Improvement --- p.60Chapter 5.1 --- Introduction --- p.60Chapter 5.2 --- Sample Selection --- p.61Chapter 5.2.1 --- General Sample Selection --- p.62Chapter 5.2.2 --- Objective Evaluation Metrics --- p.65Chapter 5.2.3 --- Sample Selection For Transparency Improvement --- p.66Chapter 5.2.4 --- Theoretical Analysis of Sample Selection --- p.87Chapter 5.3 --- Frame Sclcction --- p.90Chapter 5.3.1 --- General Frame Selection --- p.91Chapter 5.3.2 --- Frame Selection For Transparency Improvement --- p.94Chapter 5.4 --- Watermark Information Retrieve --- p.103Chapter 6 --- Psychoacoustic Model For Robustness Verification --- p.105Chapter 6.1 --- Introduction of Human Auditory System --- p.106Chapter 6.1.1 --- Absolute Hearing Threshold --- p.106Chapter 6.1.2 --- Critical Bands --- p.108Chapter 6.1.3 --- Masking Effect --- p.111Chapter 6.2 --- Psychoacoustic Model of Human Auditory System --- p.112Chapter 6.3 --- Robustness Verification by Psychoacoustic Model Analysis --- p.117Chapter 7 --- Conclusions and Suggestions For Future Research --- p.121Chapter 7.1 --- Conclusions --- p.121Chapter 7.2 --- Suggestions For Future Research --- p.123Bibliography --- p.12

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas