Lossless Information Hiding in Images (häftad)
Format
Häftad (Paperback)
Språk
Engelska
Antal sidor
432
Utgivningsdatum
2016-11-11
Upplaga
UK ed.
Förlag
Syngress
Medarbetare
Guo, Shi-Ze
Illustrationer
Black & white illustrations
Dimensioner
228 x 184 x 31 mm
Vikt
889 g
Antal komponenter
1
Komponenter
3:B&W 7.5 x 9.25 in or 235 x 191 mm Perfect Bound on White w/Gloss Lam
ISBN
9780128120064
Lossless Information Hiding in Images (häftad)

Lossless Information Hiding in Images

Microbial Toxins : Tools in Enzymology

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Lossless Information Hiding in Images introduces many state-of-the-art lossless hiding schemes, most of which come from the authors' publications in the past five years. After reading this book, readers will be able to immediately grasp the status, the typical algorithms, and the trend of the field of lossless information hiding.

Lossless information hiding is a technique that enables images to be authenticated and then restored to their original forms by removing the watermark and replacing overridden images. This book focuses on the lossless information hiding in our most popular media, images, classifying them in three categories, i.e., spatial domain based, transform domain based, and compressed domain based. Furthermore, the compressed domain based methods are classified into VQ based, BTC based, and JPEG/JPEG2000 based.

  • Focuses specifically on lossless information hiding for images
  • Covers the most common visual medium, images, and the most common compression schemes, JPEG and JPEG 2000
  • Includes recent state-of-the-art techniques in the field of lossless image watermarking
  • Presents many lossless hiding schemes, most of which come from the authors' publications in the past five years
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Övrig information

Prof. Zhe-Ming Lu is currently the IEEE senior member and the Professor in Zhejiang University. He received the B.S. and M.S. degrees in electrical engineering and the Ph.D. degree in measurement technology and instrumentation from the Harbin Institute of Technology (HIT), Harbin, China, in 1995, 1997, and 2001, respectively. He became a Lecturer with HIT in 1999. Since 2003, he has been a Professor with the Department of Automatic Test and Control, HIT. He is currently a Full Professor with the School of Aeronautics and Astronautics, Zhejiang University. In the areas of multimedia signal processing and information hiding, he has published more than 250 papers, seven monographs in Chinese, one monograph in English and three book chapters in English. His current research interests include multimedia signal processing, information security, and complex networks Prof. Shi-Ze Guo is currently the assistant of the Director of One of Research Institutes of The General Staff Headquarters, and the part-time Professor in Beijing University of Posts and Communications. He received the Ph.D. degree in measurement technology and instrumentation from the Harbin Institute of Technology (HIT), Harbin, China, in 1994. He is currently also the part-time Professor in University of Science and Technology of China, Zhejiang University and Wuhan University. His current research interests include network security, information security, and complex networks. He has undertaken many national and military projects. He won the second prize of Science and Technology of China for four times, the first prize of Science and Technology of Army for 8 times. He won the Qiushi Excellent Youth Award of China Association for Science and Technology in 2011, and the 11th Chinese Youth Award of Science and Technology in 2009. He has published 2 edited books and 50 papers in the area of Information and Network Security.

Innehållsförteckning

Chapter 1. Introduction Chapter 2. Lossless Information Hiding in Images on the Spatial Domain Chapter 3. Lossless Information Hiding in Images on Transform Domains Chapter 4. Lossless Information Hiding in Vector Quantization Compressed Images Chapter 5. Lossless Information Hiding in Block Truncation Coding-Compressed Images Chapter 6. Lossless Information Hiding in JPEG- and JPEG2000-Compressed Images