By Husrev T. Sencar
Multimedia applied sciences have gotten extra subtle, allowing the net to house a speedily turning out to be viewers with an entire diversity of prone and effective supply tools. even if the net now places conversation, schooling, trade and socialization at our finger assistance, its fast progress has raised a few weighty defense issues with admire to multimedia content material. The vendors of this content material face huge, immense demanding situations in safeguarding their highbrow estate, whereas nonetheless exploiting the web as an enormous source for commerce.
Data Hiding basics and functions specializes in the idea and state of the art purposes of content material defense and knowledge hiding in electronic multimedia. one of many pillars of content material defense options is the imperceptible insertion of knowledge into multimedia information for safety reasons; the assumption is this inserted info will permit detection of unauthorized usage.
* presents a theoretical framework for information hiding, in a sign processing context;
* sensible purposes in safe, multimedia delivery;
* Compression powerful information hiding;
* info hiding for evidence of ownership--WATERMARKING;
* information hiding algorithms for picture and video watermarking.
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Extra info for Data Hiding - Fundamentals and Applications
Furthermore, at low WNR, range hiding is not possible. Since type III is a superset of type I and type II methods, its optimal version can achieve the capacity at all WNRs. A detailed analysis of type I embedding/detection and capacity results can be found in , , , . CHAPTER Type I (Linear) Data Hiding Most promising data hiding applications—like authentication, copyright control, and ownership verification—involve multimedia data and assume the presence of a very powerful attacker.
The bandwidth is dual to embedding signal size, as they are both resources of the communication, and the measure of signal-to-noise ratio (SNR) corresponds to the measure of embedding-distortion to attackdistortion ratio (watermark-to-noise ratio [WNR]). Table 3-1 shows the duality between the communications and data hiding frameworks. 2, encoding and decoding of a message index relies on proper selection of the codeword. TABLE 3-1 Duality Between Communications and Data Hiding Frameworks COMMUNICATIONS FRAMEWORK DATA HIDING FRAMEWORK Side information Host signal Encoder/decoder Embedder/detector Channel noise All forms of modification on the stego signal (attack) Power constraints Perceptual distortion limits Bandwidth Embedding signal size Signal-to-noise ratio Embedding distortion to attack distortion ratio 36 CHAPTER 3 Communication with Side Information and Data Hiding Correspondingly, in the dual data hiding problem, the performance of an embedding and detection technique depends on the underlying codeword generation scheme.
Chen et al. , Ramkumar et al. , Eggers et al. , and Perez-Gonzalez et al.  respectively, proposed methods to handle codebook generation by uniform scalar quantization. 2 based on the design of the embedder/detector pair, namely type I, type II, and type III , . Type I methods refer to additive schemes in which the stego signal is generated by adding the watermark signal to the host signal , , , , . This type of method suffers severely from host signal interference due to the nonoptimal design that assumes the host signal C to be a noise and tries to cancel it.
Data Hiding - Fundamentals and Applications by Husrev T. Sencar