Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

From the Publisher:
Steganography, a means by which two or more parties may communicate using "invisible" or "subliminal" communication, and watermarking, a means of hiding copyright data in images, are becoming necessary components of commercial multimedia applications that are subject to illegal use. This new book is the first comprehensive survey of steganography and watermarking and their application to modern communications and multimedia. 

Handbook of Information Hiding: Steganography and Watermarking helps you understand steganography, the history of this previously neglected element of cryptography, the hurdles of international law on strong cryptographic techniques, a description of possible applications, and a survey of the methods you can use to hide information in modern media. Included in this discussion is an overview of "steganalysis," methods which can be used to break steganographic communication.

This comprehensive resource also includes an introduction to and survey of watermarking methods, and discusses this method's similarities and differences to steganography. You gain a working knowledge of watermarking's pros and cons, and you learn the legal implications of watermarking and copyright issues on the Internet.

Information Hiding Techniques for Steganography and Digital Watermarking

http://blog.ncue.edu.tw/sys/lib/read_attach.php?id=11931

Hiding data in images by simple LSB substitution

Review: Digital image steganography: Survey and analysis of current methods

We present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.

Spread spectrum image steganography

We introduce a new multiresolution watermarking method for digital images. The method is based on the discrete wavelet transform (DWT). Pseudo-random codes are added to the large coefficients at the high and middle frequency bands of the DWT of an image. It is shown that this method is more robust to often proposed methods to some common image distortions, such as the wavelet transform based image compression, and image halftoning. Moreover, the method is hierarchical. The computation load needed to detect the watermark depends on the noise level in an image.

A multiresolution watermark for digital images

Publisher Summary Noise occurs in images for many reasons. Probably the most frequently occurring noise is additive Gaussian noise. It is widely used to model thermal noise and, under some often reasonable conditions, is the limiting behavior of other noises, e.g., photon counting noise and film grain noise. Gaussian noise is a part of almost any signal. For example, the familiar white noise on a weak television station is well modeled as Gaussian. Since image sensors must count photons—especially in low-light situations—and the number of photons counted is a random quantity, images often have photon counting noise. The grain noise in photographic films is sometimes modeled as Gaussian and sometimes as Poisson. Many images are corrupted by salt and pepper noise, as if someone had sprinkled black and white dots on the image. Other noises include quantization noise and speckle in coherent light situations.

Image Noise Models

In this paper, we introduce a new multiresolution watermarking method for digital images. The method is based on the discrete wavelet transform (DWT). Pseudo-random codes are added to the large coefficients at the high and middle frequency bands of the DWT of an image. It is shown that this method is more robust to proposed methods to some common image distortions, such as the wavelet transform based image compression, image rescaling/stretching and image halftoning. Moreover, the method is hierarchical.

Wavelet transform based watermark for digital images.

A new class of rank-order-based filters, called lower-upper-middle (LUM) filters, is introduced. The output of these filters is determined by comparing a lower- and an upper-order statistic to the middle sample in the filter window. These filters can be designed for smoothing and sharpening, or outlier rejection. The level of smoothing done by the filter can range from no smoothing to that of the median filter. This flexibility allows the LUM filter to be designed to best balance the tradeoffs between noise smoothing and signal detail preservation. LUM filters for enhancing edge gradients can be designed to be insensitive to low levels of additive noise and to remove impulsive noise. Furthermore, LUM filters do not cause overshoot or undershoot. Some statistical and deterministic properties of the LUM filters are developed, and a number of experimental results are presented to illustrate the performance. These experiments include applications to 1D signals and to images. >

Charles G. Boncelet

Papers

Spread spectrum image steganography

A multiresolution watermark for digital images

Image Noise Models

Wavelet transform based watermark for digital images.

LUM filters: a class of rank-order-based filters for smoothing and sharpening